Faculty Profiles - ZHANG Lifeng

Papers - ZHANG Lifeng

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S2DiNet: Towards lightweight and fast high-resolution dichotomous image segmentation Reviewed International journal

Chen S., Tang H., Huang Y., Zhang L., Hu X.

Pattern Recognition 164 2025.08

Point Cloud Completion of Occluded Corn with a 3D Positional Gated Multilayer Perceptron and Prior Shape Encoder Reviewed International journal

Gao Y., Li Z., Liu T., Li B., Zhang L.

Agronomy 15 ( 5 ) 2025.05

Corn pose estimation using 3D object detection and stereo images Reviewed International journal

Gao Y., Li Z., Hong Q., Li B., Zhang L.

Computers and Electronics in Agriculture 231 2025.04

A highly sensitive electrochemical immunosensor based on PET/GO/pPd/MAb nanofiber-particles for metolachlor detection Reviewed International journal

Qin Y., Jiang Y., Zheng Z., Zhou G., Zhang L., Wang C., Bian Y.

Electrochimica Acta 509 2025.01

An Adaptive and Automatic Power Supply Distribution System with Active Landmarks for Autonomous Mobile Robots Reviewed International journal

Li Z., Gao Y., Zhu M., Tang H., Zhang L.

Sensors 24 ( 18 ) 2024.09

Extraction of Corn Plant Phenotypic Parameters with Keypoint Detection and Stereo Images Reviewed International journal

Gao Y., Li Z., Li B(Yangzhou University)., Zhang L.

Agronomy 14 ( 6 ) 2024.06

6DoF-3D: Efficient and accurate 3D object detection using six degrees-of-freedom for autonomous driving Reviewed International journal

Li Z., Yang Z., Gao Y., Du Y(Yangzhou University)., Serikawa S., Zhang L.

Expert Systems with Applications 238 2024.03

Keypoint3D: Keypoint-Based and Anchor-Free 3D Object Detection for Autonomous Driving with Monocular Vision Reviewed

Li Z., Gao Y., Hong Q.(Yangzhou University), Du Y.(Yangzhou University), Serikawa S., Zhang L.

Remote Sensing 15 ( 5 ) 2023.03

A Method to Automatic Create Dataset for Training Object Detection Neural Networks Reviewed International journal

Zhou S., Yang Z., Zhu M., Li H., Serikawa S., Mizumachi M., Zhang L.

IEEE Access 10 80505 - 80517 2022.08

Person re-identification in the real scene based on the deep learning Reviewed International journal

Miaomiao Zhu, Shengrong Gong, Zhenjiang Qian, Seiichi Serikawa & Lifeng Zhang

Artificial Life and Robotics ( Springer ) 26 ( 4 ) 396 - 403 2021.07

Authorship：Last author Language：English Publishing type：Research paper (scientific journal)

Person re-identification aims at automatically retrieving a person of interest across multiple non-overlapping camera views. Because of increasing demand for real-world applications in intelligent video surveillance, person re-identification has become an important computer vision task and achieved high performance in recent years. However, the traditional person re-identification research mainly focus on matching cropped pedestrian images between queries and candidates on commonly used datasets and divided into two steps: pedestrian detection and person re-identification, there is still a big gap with practical applications. Under the premise of model optimization, based on the existing object detection and person re-identification, this paper achieves a one-step search of the specific pedestrians in the whole images or video sequences in the real scene. The experimental results show that our method is effective in commonly used datasets and has achieved good results in real-world applications, such as finding criminals, cross-camera person tracking, and activity analysis.

DOI： 10.1007/s10015-021-00689-9

Kyutacar

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85110927599&origin=inward

A self-actuating and self-sensing microcantilever sensor modified by rGO-COOH@CuNPs@Ce-MOF nanocomposites for rapid detection of ALV-J Reviewed International journal

Qin Y., Zheng Z., Gu W., Bittencourt C., Jiang Y., Zhang L., Bian Y.

Chemical Engineering Journal 513 2025.06

Organometallic modification of silica with europium endowing the fluorescence properties: The key technique for numerical quality monitoring Reviewed International journal

Wu J., Zhang Y., Hong Q., Yang H., Zhang L., Zhang M., Yu L.

Chinese Chemical Letters 36 ( 4 ) 2025.04

Microwave-assisted rapid synthesis of yttrium iron garnet nano powders: formation mechanism and magnetic properties Reviewed International journal

Chen P., Yang M., Wang Y., Liu X., Wu B., Song X., Sun H., Liu J., Zhang L.

Applied Physics A Materials Science and Processing 131 ( 4 ) 2025.04

Interfacial magneto-electric synergistic strategy for enhancing microwave absorbing properties of barium hexa-ferrite by polyaniline surface modification and La-doping activation Reviewed International journal

Yang M., Liu X., Wu B., Chen W., Abdallah D., Sun H., Song X., Liu J., Zhang L., Zhang M.

Colloids and Surfaces A Physicochemical and Engineering Aspects 707 2025.02

Semi-supervised Learning-Based Passive Visible Light Positioning Using Solar Irradiation Reviewed International journal

Wen T., Sun G., Zhu M., Zhang L.

Communications in Computer and Information Science 2402 CCIS 27 - 34 2025.01

Design magneto-dielectric elastomer composites for flexible electric/magnetic field response multi-mode sensors Reviewed International journal

Zhang L., Wang Y., Ren J., Liu X., Abdallaha D., Wang H., Song X., Sun H., Zhang L., Liu J.

Polymer Composites 2025.01

Design of magnetic elastomer composites with tunable magnetic responses from soft to hard magnetization Reviewed International journal

Li Q., Wang Z., Wang Y., Liu X., Song X., Liu J., Zhang M.(Yangzhou University), Zhang L.

Materials Research Bulletin 179 2024.11

Speech emotion recognition based on multi-feature speed rate and LSTM Reviewed International journal

Yang Z., Li Z., Zhou S., Zhang L., Serikawa S.

Neurocomputing 601 2024.10

Effects of interfacial polarization induced by La doping and surface carboxylation on microwave absorption properties of BaM/PANI composites Reviewed International journal

Chen W., Yang M., Liu X., Wu B., Zheng B., Song X., Liu J., Zhang M., Zhang L.

Journal of Materials Science 59 ( 35 ) 16535 - 16550 2024.09

Non-uniform polarization boosted electromagnetic wave absorption with high efficiency and a broad frequency range Reviewed International journal

Yang M., Liu X., Wu B., Chen W., Song X., Liu J., Nan Z., Zhang M.(Yangzhou University), Zhang L.

Materials Today Chemistry 39 2024.07

A novel iron metal organic framework-based nanocomposite for the synergistic degradation and adsorption of organic pollutants and Cr (Ⅵ) under visible light Reviewed International journal

Song X., Dai R., Zhu T., Zhang S., Liu J., Zhang S., Zhang L.

Journal of Cleaner Production 456 2024.06

YOLOv8MS: Algorithm for Solving Difficulties in Multiple Object Tracking of Simulated Corn Combining Feature Fusion Network and Attention Mechanism Reviewed International journal

Gao Y., Li Z., Li B., Zhang L.

Agriculture (Switzerland) 14 ( 6 ) 2024.06

Single Object Tracking Based on Enhanced Cross Attention Reviewed International journal

Ziyang Qi, Lifeng Zhang

Proceedings of the 12th IIAE International Conference on Industrial Application Engineering 2024 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 25 - 33 2024.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan matsue 2024.03.26 - 2024.03.30

The proposal and development of Siamese Network have led to the advancement of single object tracking algorithms that take into account real-time performance while improving performance results. However, based on the features extracted by the neural network, the traditional Siamese Network method only performs the correlation operation on them, so the tracker accuracy and robustness are deficient when there are occlusions and scale changes in the tracking scene. This paper proposes to use the Attention Head Network to replace the similarity calculation operation in the Siamese Network to calculate the cross features and enhance the model discriminability; and based on this, the cross features are enhanced to compensate for the lack of cross feature fusion. Experimental validation on the OTB100 and VOT2016 datasets yields great performance. The experiment results of both datasets are improved compared to the baseline tracker show good performance in tracking scenarios such as occlusion.

DOI： 10.12792/iciae2024.006

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2024/paper/view/3026

Visual Object Tracking with Appearance Model Updating and Tracking Reinitialization Reviewed International journal

Yuya Sun, Miaomiao Zhu(Changshu Institute of Technology), Shengrong Gong, Lifeng Zhang

Proceedings of the 12th IIAE International Conference on Industrial Application Engineering 2024 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 83 - 88 2024.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan matsue 2024.03.26 - 2024.03.30

Visual object trackers based on siamese network have performed exceptionally on multiple datasets, but their robustness are still influenced by the appearance deformation and loss of the object. Firstly, to adapt to changes in appearance, we update appearance model by replacing initial object templates with current object appearance features. Referring to deep reinforcement learning, this process can be modeled to a Markov decision process. So we introduce proximal policy optimization algorithm (PPO) to optimize it. Secondly, to further deal with the inevitable tracking failure, a tracking reinitialization is proposed to speculate whether the object is lost or not. If the object is believed to be lost, the local siamese tracker would be suspended and a global tracker will be launched to search the target object. Finally, we compare the proposed tracker with some popular methods on dataset OTB-2013, OTB-2015 and GOT-10k, confirming its effectiveness and efficiency by the experimental results.

DOI： 10.12792/iciae2024.015

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2024/paper/view/3029

Boundary-Aware Multi-modal Mirror Segmentation Reviewed International journal

Haonan Tang, Shuhan Chen(Yangzhou University), Lifeng Zhang

Proceedings of the 12th IIAE International Conference on Industrial Application Engineering 2024 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 34 - 37 2024.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan matsue 2024.03.26 - 2024.03.30

Mirror segmentation is a challenging task in the field of computer vision, with the difficulty being the system's struggle to distinguish between mirror reflections and actual objects in the background of an image. Traditional methods typically rely on the contextual relationships in the image and the reflective properties of mirrors for identification. However, these approaches are susceptible to the variability of mirror placement and the randomness of objects in the scene, consequently limiting the system's recognition capabilities. Moreover, due to the high similarity between the boundaries and the background, these methods often face issues of unclear or erroneous segmentation boundaries. Research has found that mirrors exhibit more pronounced features in depth images. Based on this discovery, we propose a boundary-aware multi-modal mirror segmentation method. This method involves the use of a multi-modal feature fusion module to integrate cross-modal feature. A boundary guidance module is also employed, utilizing boundary and high-frequency information to optimize the segmentation results. Compared to traditional image segmentation methods, our multi-modal approach demonstrates significant advantages in handling mirror segmentation tasks in complex scenes, particularly in terms of boundary clarity and segmentation accuracy.

DOI： 10.12792/iciae2024.007

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2024/paper/view/3053

Optimizing Speech Emotion Recognition with Hilbert Curve and convolutional neural network Reviewed International journal

Yang Z., Zhou S., Zhang L., Serikawa S.

Cognitive Robotics 4 30 - 41 2024.01

Magnetic elastomer composites with tunable magnetization behaviors for flexible magnetic transducers Reviewed International journal

Wang Y., Wang Z., Liu X., Zhang L., Li Q., Abdallaha D., Song X., Zhang L., Sun H., Liu J.

Polymer Composites 2024.01

FSANet Stereo3D Binocular Detection Network Reviewed International journal

Yuliang Gao, Zhen Li, Aoran Xi, Yuting Wang, Lifeng Zhang

Proceedings of the 11th IIAE International Conference on Industrial Application Engineering 2023 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 110 - 113 2023.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Okinawa 2023.03.26 - 2023.03.30

Traditional binocular 3D object detection uses ResNet50 to extract multi-level features, which has the problems of lack of adaptability and loss of information. Inspired by YOLOV5, this work uses the Focus module to perform down-sampling to replace the ResNet50 network to extract multi-level information. On the other hand, the cost-volume are reweighted to get better depth. ASPP models are used for multi-dimensional object detection.The above constitutes the FSANet network.In the Kitti dataset, better results were obtained.

DOI： 10.12792/iciae2023.022

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/view/2772

Deep Learning based Single-view 3D Reconstruction: A Survey Reviewed International journal

Wenjing Bian, Dongren Liu, Yaoyao Chen, Lifeng Zhang

Proceedings of the 11th IIAE International Conference on Industrial Application Engineering 2023 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 196 - 202 2023.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Okinawa 2023.03.26 - 2023.03.30

Reconstruction 3D objects from a single view is an important research direction in computer vision. With the development of deep learning technology, a single-view 3D reconstruction based on deep learning has made remarkable progress in recent years. In reviewing 3D object reconstruction based on deep learning, firstly, the research progress of 3D reconstruction methods based on deep learning is analyzed in detail according to different representations of 3D objects, i.e., point cloud, voxel, and mesh. Secondly, the standard 3D reconstruction datasets and evaluation criteria are summarized. Finally, the challenges of 3D object reconstruction based on deep learning are summarized.

DOI： 10.12792/iciae2023.035

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/view/2783

Research on Vegetable Growth Condition based on Computer vision Reviewed International journal

Yaoyao Chen, Zijun Yang, Yuting Wang, Aoran Xi, Wenjing Bian, Lifeng Zhang

Proceedings of the 11th IIAE International Conference on Industrial Application Engineering 2023 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 137 - 142 2023.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Okinawa 2023.03.26 - 2023.03.30

This study is based on computer vision technology for soilless cultivation of vegetables. Traditional soilless culture requires human to judge the growth status of vegetables, while this study uses STM32 single-chip microcontroller as a microcontroller for environmental data collection and computer vision technology for intelligent detection of the growth status of vegetables. Finally, a comprehensive analysis of the most suitable growing conditions for vegetables. This paper focuses on the leaves of vegetables. Brassica chinensis was used as the object of study. The vegetable leaf area values were derived by different image pre-processing, segmentation, and feature extraction. For Brassica diseases, this study constructs a vegetable disease identification model based on an improved MobileNet-V2 network. This model is compared with similar network models and the speed is faster.

DOI： 10.12792/iciae2023.026

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/view/2772

Pump Fault Diagnosis Based on Time Frequency Image and Parameters Improved CNN-LSTM Network Reviewed International journal

Aoran Xi, Yueping Mo, Tian Wen, Yuting Wang, Zhen Li, Yaoyao Chen, Lifeng Zhang

Proceedings of the 11th IIAE International Conference on Industrial Application Engineering 2023 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 129 - 136 2023.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Okinawa 2023.03.26 - 2023.03.30

This paper combines the fault feature extraction and intelligent diagnosis of rolling bearings, and proposes a fault diagnosis model that combines 2D images with convolutional neural network (CNN) and long short memory network (LSTM), and optimizes the parameters. The different fault signals of rolling bearings are processed, and the processing capabilities of short-time Fourier, Wigner Ville distribution and wavelet transform for bearing signals are studied and compared. The Softmax function is used to realize multi fault pattern recognition and complete fault diagnosis. The experimental results show that the time-frequency image formed by wavelet transform has better performance on the eigenvalues of vibration signals of rotating bearings than other time-frequency image processing methods.

DOI： 10.12792/iciae2023.025

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/view/2776

Marine Life Detection Algorithm Based on Deep Convolutional Generative Adversarial Network and ResNeXt50 with FPN Faster R-CNN Network Reviewed International journal

Yuting Wang, Seiichi Serikawa, Wenwen Shen, Lifeng Zhang, Zijun Yang, Tian Wen, Aoran Xi, Yaoyao Chen

Proceedings of the 11th IIAE International Conference on Industrial Application Engineering 2023 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 121 - 128 2023.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Okinawa 2023.03.26 - 2023.03.30

The development and utilization of marine resources has always been a focus of attention, and a prerequisite for the rational development of marine resources is the understanding of the distribution of biological resources in the ocean, so the detection of marine life has become an inevitable challenge in the development of marine resources. The acquisition of marine life images by underwater cameras is particularly difficult due to the complexity of the underwater terrain and the difficulty of underwater imaging. Therefore, the detection of marine life often faces problems of difficulties in dataset acquisition, scarcity of data in the dataset and low quality of images. To address the above problems, a marine life detection algorithm based on the combination of deep convolutional generative adversarial network and ResNeXt50 with FPN Faster R-CNN network is proposed in this paper. The algorithm uses Faster R-CNN as the basic framework for marine life detection and uses deep convolutional generative adversarial network to generate data for small dataset to effectively expand the dataset without the difficulty of underwater image acquisition. For the feature extraction network, we use ResNeXt50, which employs the idea of group convolution, as the basic network for feature extraction. Then, the network is combined with feature pyramid network to enhance the feature extraction capability. The expanded dataset fed into the ResNeXt50 with FPN Faster R-CNN target detection network for training. It can be demonstrated that the detection results of expanded dataset generated by DCGAN in ResNeXt50 with FPN Faster R-CNN network is better compared to the original dataset and the Resnet50 with FPN Faster R-CNN network.

DOI： 10.12792/iciae2023.024

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/view/2772

Unsupervised Learning Based Indoor Personnel Behavior Pattern Mining Reviewed International journal

Tian Wen, Gaofei Sun, Yuting Wang, Aoran Xi, Lifeng Zhang

Proceedings of the 11th IIAE International Conference on Industrial Application Engineering 2023 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 114 - 120 2023.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Okinawa 2023.03.26 - 2023.03.30

Indoor personnel behavior is an essential part of indoor environmental monitoring. Standard indoor personnel behavior recognition methods have problems, such as invasion of privacy and high equipment costs. This paper proposes a novel, low-privacy indoor-person behavior pattern analysis method. Three types of indoor person behavior recognition methods are formed through time and frequency domain analysis. Moreover, since the model will fail in new rooms, we use unsupervised learning to perform pattern recognition on the analyzed feature data to enhance the generalization and robustness of the model. The implementation results show that our algorithm can recognize people's behavior in rooms and that the improved pattern recognition model achieves 97% results, which is significantly better than more widely used models.

DOI： 10.12792/iciae2023.023

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2023/paper/view/2772

Facilitating enhanced microwave absorption properties of barium hexaferrite/polyaniline composites based on tunable interfacial polarization by rare earth doping Reviewed International journal

Liu X., Ji R., Yang M., Chen W., Chen H., Song X., Liu J., Zhang M., Zhang L.

Journal of Alloys and Compounds 937 2023.03

Proposal for Shoplifting Detection Using Skeletal Data Assuming Surveillance Camera Footage

Fujisakia Yujin, Zhang Lifeng

Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2023 ( 0 ) 33 - 34 2023.01

Quantitative analysis of s-PB/SBR blend dispersion morphology using computer image processing-assisted Raman spectroscopic techniques Reviewed International journal

Ge M., Wu J., Hong Q., Zhang L., Zhang M., Yu L.

Analytical Methods 14 ( 40 ) 3982 - 3988 2022.09

Research on Fault Detection of Pump Rotating Bearing based on Deep Learning Reviewed International journal

Aoran Xi, Yueping Mo, Zijun Yang, Yuliang Gao, Shi Zhou, Yuting Wang, Lifeng Zhang

Proceedings of the 9th IIAE International Conference on Intelligent Systems and Image Processings 2022 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 155 - 161 2022.09

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Kobe 2022.09.06 - 2022.09.10

Large-power water pump units play an important role in factory manufacturing and social life today. The bearing failure of water pump units seriously affects the operation of water pump equipment. In order to solve the problem of pump bearing fault classification, this paper compares four diagnosis methods based on deep learning. Three kinds of input signals come from feature extraction, wavelet transform time-frequency map preprocessing, and the original signals are employed. Then establish the deep learning models of CNN and CNN-LSTM for bearing fault diagnosis. Through comparison and analysis, the accuracy of using the time-frequency wavelet transform image as input can reach 100%. Finally, by comparing the training accuracy graph, confusion matrix, and scatter plot visualization, it is proved that the time-frequency graph of wavelet transform obtains the best result.

DOI： 10.12792/icisip2022.026

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2022/paper/view/2640

Optimize YoloStereo3D Binocular Detection Network by Attention Mechanism Reviewed International journal

Yuliang Gao, Zhen Li, Aoran Xi, Yuting Wang, Lifeng Zhang

Proceedings of the 9th IIAE International Conference on Intelligent Systems and Image Processings 2022 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 117 - 120 2022.09

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Kobe 2022.09.06 - 2022.09.10

As the rapid development of computer vision, 3D object detection has become an indispensable method of perception for autonomous driving. LiDAR-only frameworks suffer from the sparsity of point clouds over the distance. While camera-only works suffer from the inaccurate depth measurement. Nevertheless, this paper proposed a LiDAR and camera fusion 3D detection framework, exploited and fused the spatiality of point clouds and the dense texture information of images together. Besides, we also utilized an automatic LiDAR and camera calibration method to ensure the accurate measurement while applied in embedded computation platform. Our experimental evaluation on KITTI dataset, the proposed work achieved good results on 3D detection accuracy and the automatic calibration method also made our work more stable and robust for different scenes.

DOI： 10.12792/icisip2022.020

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2022/paper/view/2676

The Fusion Thoughts in 3D Object Detection for Autonomous Driving: A Survey Reviewed International journal

Zhen Li, Shi Zhou, Yuliang Gao, Yuting Wang, Yuren Du, Seiichi Serikawa, Lifeng Zhang

Proceedings of the 9th IIAE International Conference on Intelligent Systems and Image Processings 2022 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 108 - 116 2022.09

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Kobe 2022.09.06 - 2022.09.10

DOI： 10.12792/icisip2022.019

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2022/paper/view/2652

Research on Two-stage Target Detection Algorithm and its Feature Extraction Network based on Deep Learning Reviewed International journal

Yuting Wang, Seiichi Serikawa, Wenwen Shen, Lifeng Zhang, Chao Yuan, Zhen Li, Shi Zhou

Proceedings of the 9th IIAE International Conference on Intelligent Systems and Image Processings 2022 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 139 - 145 2022.09

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kobe 2022.09.06 - 2022.09.10

Deep learning two-stage target detection algorithms have been widely used in the field of target detection relying on the advantages of high accuracy. This paper introduces four common two-stage target detection algorithms in detail: R-CNN, Fast R-CNN, Faster R-CNN and Mask R-CNN, and expounds their respective algorithm steps, advantages and disadvantages. At the same time, the feature extraction network that is often used in the current two-stage target detection algorithm is analyzed and summarized from two directions. One direction is to pursue image classification networks with deeper and more complex network structures and higher detection accuracy for feature extraction, such as AlexNet, VGGNet, GoogleNet, ResNet and DenseNet. Another direction is to solve the problem that the network parameters are too large and the detection speed is too slow, a lightweight neural network is proposed, hoping to reduce the parameter calculation amount of the neural network and speed up the detection speed of the network, such as SqueezeNet, MobileNet, ShuffleNet and GhostNet. This paper introduces the network structure of the above nine networks and their respective advantages and disadvantages from the above two directions, and provides a theoretical and method reference for the selection of the feature extraction network of the two-stage target detection algorithm.

DOI： 10.12792/icisip2022.024

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2022/paper/view/2634

Research on Marine Life Detection Algorithm Based on Deep Learning Reviewed International journal

Yuting Wang, Seiichi Serikawa, Wenwen Shen, Lifeng Zhang, Zijun Yang, Yuliang Gao, Aoran Xi

Proceedings of the 9th IIAE International Conference on Intelligent Systems and Image Processings 2022 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 133 - 138 2022.09

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kobe 2022.09.06 - 2022.09.10

Marine life detection based on deep learning has always been the focus and difficulty in the field of deep learning target detection. There are two main problems. First, underwater imaging often has problems such as low image contrast, blurred image, color shift, and blue-green tint of the background. How to solve these problems in imaging. Second, there are many algorithms in the field of deep learning target detection, how to choose a suitable algorithm for marine life detection. Aiming at the above problems, this paper firstly introduces three algorithms suitable for underwater image enhancement: the method based on dark channel prior, the method based on histogram equalization and the method based on Retinex. Then, six commonly used deep learning target detection algorithms are introduced from two aspects: target detection algorithm based on candidate region proposal and target detection algorithm based on regression: R-CNN, Fast R-CNN, Faster R-CNN, Mask R-CNN, YOLO, SSD, and each analyzes their advantages and disadvantages. It provides a theoretical and method reference for deep learning-based marine biological detection.

DOI： 10.12792/icisip2022.023

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2022/paper/view/2633

Design of Control System for Vegetable Soilless Culture Reviewed International journal

Yaoyao Chen, Zijun Yang, Shi Zhou, Aoran Xi, Yuting Wang, Zhang Lifeng

Proceedings of the 9th IIAE International Conference on Intelligent Systems and Image Processings 2022 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 146 - 154 2022.09

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Kobe 2022.09.06 - 2022.09.10

This design combines the automation control technology with the latest soilless cultivation technology to make the vegetable transparent and controllable in all aspects of the whole growth cycle. It is different from the current technology. It is more innovative to modularize the cultivation unit and monitoring unit , so that its application scope is greatly expanded. Under certain conditions, it can also be added as a subsystem of other systems. With application, based on array distributed sensors and algorithm, the atomization of nutrient solution is controlled to optimize the nutrient conditions and make the growth state of vegetables best. Considering the economy and practicability of the actual construction of the system, Proteus and the C language is used to simulate the circuits in the design process, construction of the project fully ensure the reliability of the system and the transplant of the multi-platform environment.

DOI： 10.12792/icisip2022.025

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2022/paper/view/2638

Identifying User's Smartphone Possession Location and Behavior Including Untrained Classes by Using Deep Metric Learning Reviewed

Rui Kitahara, Lifeng Zhang

Proceedings of the 10th IIAE International Conference on Industrial Application Engineering 2022 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 213 - 219 2022.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Matsue 2022.03.26 - 2022.03.31

In our previous study,(1) we confirmed that it was possible to classify the user’s smartphone possession location and behavior simultaneously using Mdk-ResNet.(2) However, there was a problem that when untrained classes were given as input, it was impossible to output them as unknown classes using normal classifications as in our and other’s previous studies. Therefore, this time, we aimed to output untrained data as an unknown class by learning the distance between images using deep metric learning, and not only classifying the learned classes. In this study, we used a smartphone’s accelerometer to acquire the data of experimental participants and created a trained model by learning through deep metric learning. We classified the user’s smartphone possession location and behavior, including the unknown class of unlearned data, by calculating the cosine similarity between the image vector prepared in advance and the image vector output from the trained model during inference using the trained model. As a result, we confirm not only that the untrained data can be output as the unknown class, but also that the accuracy is comparable to the previous study.

DOI： 10.12792/iciae2022.039

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2022/paper/view/2604

Research Status of Fault Diagnosis of Large and Medium-sized Vertical Water Pump Units Reviewed International journal

Aoran Xi, Lifeng Zhang, Yueping Mo

Proceedings of the 10th IIAE International Conference on Industrial Application Engineering 2022 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 156 - 161 2022.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Matsue 2022.03.26 - 2022.03.31

This paper analyzes the development process and status quo of the fault diagnosis technology of vertical water pump units. Several common fault detection methods of vertical water pump units are introduced in detail from the analytical model-based processing method, signal-based processing method, and knowledge-based processing method. The advantages and disadvantages are analyzed and summarized, providing theoretical methods for fault diagnosis of large and medium-sized vertical water pump units.

DOI： 10.12792/iciae2022.028

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2022/paper/view/2598

An Adaptive Threshold Canny Edge Detection Method for Applications with Simple Background Reviewed

Shi Zhou, Zijun Yang, Zhen Li, Yuliang Gao, Seiichi Serikawa, Mitsunori Mizumachi, Lifeng Zhang

Proceedings of the 10th IIAE International Conference on Industrial Application Engineering 2022 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 123 - 128 2022.03

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

Japan Matsue 2022.03.26 - 2022.03.31

Edge detection is an important image processing problem with many practical applications in different fields. While many methods have been proposed, further improvements still need to be made for specific applications. This paper focuses on the application of Canny edge in the image with a simple background, proposed an adaptive threshold Canny edge detection method. Considering the distribution of the object and the solid-color background, a pixels intensity statistic is operated for the corresponding gray image. In this way, the double thresholds are determined by analyzing the statistical result. Furthermore, to verify the effectiveness of the proposed method, experiments are done on images that are taken with different conditions. The result shows that Canny edge can be well detected by utilizing the two adaptive threshold values and have strong robustness to different conditions. Particularly in the applications, such as object detection and image segmentation, the adaptive threshold Canny edge detection method plays a meaningful role.

DOI： 10.12792/iciae2022.023

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2022/paper/view/2597

Person Re-identification for Real-time Video Surveillance Based on Deep Learning Reviewed International journal

Miaomiao Zhu, Shengrong Gong, Zhenjiang Qian, Seiichi Serikawa, Lifeng Zhang

Proceedings of the Joint Symposium of The Twenty-Seventh International Symposium on Artificial Life and Robotics (AROB 27th 2022) ( International Society of Artificial Life and Robotics ) 98 - 103 2022.01

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

日本別府 2022.01.25 - 2022.01.27

Person re-identification (ReID), as an instance-level recognition problem, aims at automatically retrieving a person- of-interest across multiple non-overlapping camera views, which is considered as a sub problem of image retrieval. Unlike the traditional ReID research, the proposed system aims to combine pedestrian detection and ReID to perform one-step pedestrian detection and search. For real-time video surveillance obtained by cameras distributed in different locations, given a person-of- interest to be queried, the goal of our method is to search a person from the whole scene images or videos directly instead of matching them with manually cropped pedestrians in the existing datasets. To further verify the effectiveness of the proposed method in the real scene，many experimental datasets of complex scenes are collected respectively. Finally, the experimental results show that our method is effective in commonly used datasets and has achieved good results for real-time video surveillance in the real scene.

Identification of Rice Disease with Shuffle Attention & Inception Reviewed International journal

Yuliang Gao1, Zhen Li, Lifeng Zhang, Seiichi Serikawa, Xiangying Xu, Bin Li

Language：English Publishing type：Research paper (international conference proceedings)

日本別府 2022.01.25 - 2022.01.27

This paper presents an identification algorithm of rice diseases and insect pests based on a convolutional neural net- work. It aims to solve the problems of a large number of parameters and the low accuracy of the traditional algorithm. The Inception-ResNetV1 module and the shuffle attention module are combined. It achieves the effects of significantly reducing parameters and improving accuracy. And this model is trained by SAM optimizer to get a better result. Compared with tradi- tional models ResNet50 & Inception-ResNetV1, the highest accuracy reaches 95.66%, the parameters in the self-made dataset decreased by 47.6% and 34.02%, and the accuracy increased by 1.91% and 1.32%, respectively.

Proposal for a system for visually impaired people to identify products in stores Reviewed International journal

Tomoyuki Zaizen, Rui Kitahara, Lifeng Zhang

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

日本別府 2022.01.25 - 2022.01.27

In recent years, Japan has been facing the problem of an aging population due to the aging of society. In addition, many elderly people are visually impaired, and the number of visually impaired people is expected to increase in the future. However, the aging society is also facing a shortage of caregivers, as the elderly must care for the elderly. Therefore, the problem of not having enough people to care for the increasing number of visually impaired people will arise in Japan in the future. The shortage of caregivers may lead to the tendency of the elderly visually impaired to refrain from going out. Therefore, a system that allows the visually impaired to live without care is needed to prevent this.
Prior work includes a system that identifies products using image processing techniques, namely motion detection and image classification using machine learning techniques. However, in the system of this previous research, the number of products that can be identified is as few as six, and the product identification rate is not sufficiently high.
Therefore, in this research, we attempted to increase the number of products that can be identified and also to improve the identification rate of the products.

The Hilbert Curve-based Speech Signal Visualization for Speech Emotion Recognition Reviewed International journal

Zijun Yang, Lifeng Zhang, Shi Zhou, Seiichi Serikawa

Language：English Publishing type：Research paper (international conference proceedings)

日本別府 2022.01.25 - 2022.01.27

This paper proposed a method to convert the one-dimensional speech signal into two-dimensional image signal, so that the mature image processing skills can be used to analysis speech signal and implement speech emotion recognition. The article uses the Hilbert Curve which can fill the entire space and give a mapping between one-dimensional and two-dimensional space. Moreover, to better illuminate the effectiveness of the proposed method, we use the proposed method convert the six emotion language signals dataset into the images, and a neural network is trained on the created dataset. The result shows that the trained model can achieve an accuracy rate of 51.7%. It means use the method that convert the speech signal into image signal implement speech emotion recognition is well. In the follow-up, we will further optimize the algorithm to improve the accuracy.

Behavioral Recognition Considering Multiple Possession Positions Using Smartphone Accelerometers by Transfer Learning Reviewed International journal

Rui Kitahara, Lifeng Zhang

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

日本別府 2022.01.25 - 2022.01.27

With the widespread use of smartphones and wearable devices in recent years, various applications have been devel- oped to use their built-in sensors.Among them, HAR (Human Activity Recognition) using accelerometers has the advantage of privacy protection compared to camera-based data acquisition.Therefore, it is thought a good approach to watch over the elderly who live alone in the coming elder society.However, most of the behavior recognition has been done by fixing the possession position of the smartphone in one place, measuring the data, and recognizing the behavior.However, this is not according to the actual situation because people carry smartphones around in different places.Therefore, the purpose of this study is to recognize behavior by considering various possession positions. In this study, we set up four different positions for smartphone posses- sion. And we set up three different behavior. By combining all of the possession positions (4 types) and behaviors (3 types), we created a data set with 12 classes for classification. After data measurement, the measured time-series data were converted into 2D images using the GAF[1] algorithm as a preprocessing step.Then, the time-series data, which became 2D images, were trained with Mdk-ResNet[2] for classification. The dataset created in this study has a smaller number of datasets compared to previous studies.Therefore, in this study, we further aimed to improve the accuracy by also performing transfer learning.In this study, we created the Mdk-ResNet trained model using the WISDM dataset, a large-scale behavioral dataset frequently used in behavioral recognition research, and performed transfer learning.As a result, the results were Accuracy:0.9899, F1:0.9890, Recall:0.9895, and Precision:0.9887, when not using the transfer learning. This result indicates that recognition was possible with relatively high accuracy.In addition, by using transfer learning, we could obtain Accuracy:0.9921,F1:0.9913,Recall:0.9913 and Precision:0.9905, which was even higher recognition accuracy.

A Keypoint-Based and Anchor-Free 3D Detection for Autonomous Driving Using Monocular Camera Reviewed International journal

Zhen Li, Yuliang Gao, Qingqing Hong, Yuren Du, Seiichi Serikawa and Lifeng Zhang

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

日本別府 2022.01.25 - 2022.01.27

Autonomous driving technology has received great attention from scientific research and social marketing. 3D object detection technology is the core research topic of autonomous driving. Nowadays, most 3D object detection researches heavily depend on lidar and radar sensors, which could directly offer depth information. However, inspired by human driving experiences, 3D world perception can be obtained by pure visual scheme. This paper proposed an anchor-free and keypoint-based 3D object detection framework using a monocular camera. Our work took CenterNet as baseline and made several improvements to achieve better 3D detection performance. First, we utilized the rotation angle regression method in polar coordinate system, which has simplified the original framework greatly. Then, we proposed the ellipse Gaussian Filter method to fit the ground truth rectangular boxes much more better. Finally, this paper also improved the backbone network of DLA-34, the more complex neural network performances better in complex 3D detection task. Our proposed framework can improve 3D detection by 6.9% in pedestrian classification. And the whole detection performance, including 2D detection, also improved to 97.8% for vehicles.

Self-Supervised Visual Odometry Based on the Projection of Reliable Pixels Reviewed International journal

Shi Zhou, Zijun Yang, He Li, Seiichi Serikawa, Mitsunori Mizumachi and Lifeng Zhang

Authorship：Last author Language：English Publishing type：Research paper (international conference proceedings)

日本別府 2022.01.25 - 2022.01.27

Complex outdoor environment includes variable lighting, moving objects and direct sunlight, visual odometry in outdoor environments remains a challenging problem. In this work, a self-supervised pose estimation network is trained based on the projection between adjacent frames. The pose between two adjacent frames is a 6D vector. It can be solved with a part of effective pixels instead of all the pixels. Thus, only reliable pixels are under consideration when training. To eliminating the influence of unreliable pixels, outside mask and poor projection mask are proposed to check them out. Furthermore, we evaluated the proposed method on the KITTI datasets and compared it with other deep learning-based visual odometry methods. The result shows that the proposed method can detect poor projection and outside pixels well. Moreover, it achieves higher accuracy pose estimation.

Higher accuracy self-supervised visual odometry with reliable projection Reviewed International journal

Zhou S., Yang Z., Zhu M., Li H., Serikawa S., Mizumachi M., Zhang L.

Artificial Life and Robotics 2022.01

A survey of 3D object detection algorithms for intelligent vehicles development Reviewed International journal

Zhen Li, Yuren Du, Miaomiao Zhu, Shi Zhou & Lifeng Zhang

Artificial Life and Robotics ( Springer ) 27 ( 1 ) 115 - 122 2021.11

Authorship：Last author Language：English Publishing type：Research paper (scientific journal)

With the rapid development of Artificial Intelligent algorithms on Computer Vision, 2D object detection has greatly succeeded and been applied in various industrial products. In the past several years, the accuracy of 2D object detection has been dramatically improved, even beyond the human eyes detection ability. However, there is still a limitation of 2D object detection for the applications of Intelligent Driving. A safe and reliable self-driving car needs to detect a 3D model of the around objects so that an intelligent driving car has a perception ability to real driving situations. This paper systematically surveys the development of 3D object detection methods applied to intelligent driving technology. This paper also analyzes the shortcomings of the existing 3D detection algorithms and the future development directions of 3D detection algorithms on intelligent driving.

DOI： 10.1007/s10015-021-00711-0

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85118385846&origin=inward

A 3D Object Detection Framework for Intelligent Driving using YOLOv4 Reviewed International journal

Zhen Li, Yuren Du, Qingqing Hong, Seiichi Serikawa, Lifeng Zhang

Proceedings of the 8th IIAE International Conference on Intelligent Systems and Image Processings 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 9 - 15 2021.09

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kobe 2021.09.06 - 2021.09.10

As the continuous evolution of the vehicles' industry, the self-driving technology has become an indispensable part in today's intelligent vehicles. While 3D object detection is the most core technique in the self-driving technology. A little improvement in the accuracy and efficiency of a 3D object detector will be of the utmost importance to intelligent driving and human life. So this paper focused on the improvement of detecting accuracy based on the yolov4, which is also an effective object detection network. This work transformed yolov4 from a 2D detector into a 3D detector, and also improved the original yolov4 neural network with the CSPDarknet53 backbone network. The proposed framework has a more effective and accurate performance in the 3D object detecting for intelligent driving.

DOI： 10.12792/icisip2021.004

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2021/paper/view/2495

Behavioral Estimation for Multiple Possession Positions Using Smartphone Accelerometers Reviewed International journal

Rui Kitahara, Lifeng Zhang

Proceedings of the 8th IIAE International Conference on Intelligent Systems and Image Processings 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 171 - 174 2021.09

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kobe 2021.09.06 - 2021.09.10

In recent years, with the widespread use of smartphones and wearable devices, a variety of research has been conducted using built-in sensors. For example, height estimation and road condition estimation have been conducted. In addition, behavioral estimation of the smartphone holder, possession position estimation, and person estimation have also been conducted. However, most of them measure data by fixing the possession position at a single location, and do not take the possession position into account when estimating behavior. In this research, we aim to estimate the behavior of a person by considering multiple possession positions, because it is necessary to estimate the behavior of a person by considering various possession positions when actually using behavior estimation as a system. In addition, by treating the time series data acquired by the 3-axis acceleration sensor of a smartphone as a 2-dimensional image using the GAF algorithm,(1) class classification by machine learning is performed.

DOI： 10.12792/icisip2021.030

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2021/paper/view/2560

Rice Disease and Insect pest Identifition Algorithm with Shuffle Attention Mechanism Reviewed International journal

Yuliang Gao, Lifeng Zhang, Li Bin

Proceedings of the 8th IIAE International Conference on Intelligent Systems and Image Processings 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 159 - 164 2021.09

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kobe 2021.09.06 - 2021.09.10

This paper presents an identififition algorithm of rice diseases and insect pests based on convolutional neural network. Aiming at the problems of large amount ofparameters and low accuracy of traditional algorithm. The traditional convolution neural network Inception-ResNetV2 and the shuffle attention module are combined. It achievesthe effects of greatly reducing parameters and obviously improving accuracy. Compared with traditional models ResNet50 and Inception-ResNetV2, the highest accuracyreaches 95.24%, the parameters in the self-made data set decreased by 47.6% and 34.02%, and the accuracy increased by 1.49% and 0.9%, respectively.

DOI： 10.12792/icisip2021.028

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2021/paper/view/2480

Self-supervised monocular depth estimation with occlusion mask and edge awareness Reviewed International journal

Shi Zhou, Miaomiao Zhu, Zhen Li, He Li, Mitsunori Mizumachi, Lifeng Zhang

Artificial Life and Robotics ( Springer ) 26 ( 3 ) 354 - 359 2021.05

Authorship：Last author Language：English Publishing type：Research paper (scientific journal)

Depth estimation is one of the basic and important tasks in 3D vision. Recently, many works have been done in self-supervised depth estimation based on geometric consistency between frames. However, these research works still have difficulties in ill-posed areas, such as occlusion areas and texture-less areas. This work proposed a novel self-supervised monocular depth estimation method based on occlusion mask and edge awareness to overcome these difficulties. The occlusion mask divides the image into two classes, making the training of the network more reasonable. The edge awareness loss function is designed based on the edge obtained by the traditional method, so that the method has strong robustness to various lighting conditions. Furthermore, we evaluated the proposed method on the KITTI datasets. The occlusion mask and edge awareness are both beneficial to find corresponding points in ill-posed areas.

DOI： 10.1007/s10015-021-00685-z

Kyutacar

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85106505382&origin=inward

Proposal of Cursor Operation Method by Facial Movements for the Handicapped Reviewed

Shunya Mito, Lifeng Zhang

Proceedings of the 9th IIAE International Conference on Industrial Applications Engineers 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 3 - 7 2021.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kitakyushu 2021.03.26 - 2020.03.30

In recent years, the number of people with physical disabilities has been on the rise, with about half of them being physically disabled limb. A physically disabled person is a person with a physical disability that interferes with daily life, such as missing or malfunctioning fingers. This study focused on the use of computers in daily life. A person with a limb disability used a PC.Earlier studies that made "eye contact", "voice input", "facial expressions using a 3D camera". Those problems are the need to keep the distance between the face and the camera constant, the inability to protect privacy when people are around, and that 3D cameras are difficult and expensive to install. In this study, by using a webcam as input and machine learning, image processing techniques. Developing a system that allows a handicapped person to operate a computer with only facial movements without the use of arms or hands. We also evaluated the operability, improving the problems of previous studies.

DOI： 10.12792/iciae2021.003

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2021/paper/view/2396

Speech Sentiment Analysis Based on Basic Characteristics of Speech Signal Reviewed

Zijun Yang, Lifeng Zhang, Seiichi Serikawa

Proceedings of the 9th IIAE International Conference on Industrial Applications Engineers 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 259 - 263 2021.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kitakyushu 2021.03.26 - 2020.03.30

As the pace of life continues to accelerate, people's life pressure is increasing. With the accumulation of time, people's mental and psychological conditions have been affected to a certain extent. These mental illnesses will not cause any impact under normal circumstances, but once they break out, they will cause trauma that cannot be ignored in life or even in society. Therefore, we hope to design a system program that can chat with humans in daily life, and it can feel the human's emotional changes in daily conversations. When humans have negative emotions, it can comfort us in time and even warn humans when our negative emotions reach a certain limit. When humans have positive emotions, it can give humans affirmative approval and encouragement. Based on this concept, we must first analyze the different emotions that humans design in daily conversations. This article is mainly based on the basic characteristics of audio signals to judge the user's emotional changes. The database we use is six different emotional voices recorded by four voice actors, and each voice contains 50 single sentences for emotional recognition analysis.

DOI： 10.12792/iciae2021.047

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2021/paper/view/2445

Proposal of Information Addition Method to Existing Signs for Autonomous Driving Reviewed

Koho Futatsuishi, Lifeng Zhang

Proceedings of the 9th IIAE International Conference on Industrial Applications Engineers 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 101 - 106 2021.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kitakyushu 2021.03.26 - 2020.03.30

Automatic driving technology is developing in recent years. High level automatic driving use raders and cameras,etc to grasep the surrounding environment. Recognition of road signs is one of them. However, in the recognition of the sign, there is a problem that a similar shape things is erroneously recognized in the current method of judging by an external feature. In this research, we propose a system that recognizes road signs by reading a QR code made of a polarizing plate.

DOI： 10.12792/iciae2021.019

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2021/paper/view/2405

Prevention of Forgetting Shopping Items in Response to Shopping List Ambiguity Reviewed

Yoshihisa Igimi, Lifeng Zhang

Proceedings of the 9th IIAE International Conference on Industrial Applications Engineers 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 97 - 100 2021.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kitakyushu 2021.03.26 - 2020.03.30

Shopping plays a critical role in daily life, and also it is a time-consuming activity. For the coming elder society in Japan, the elders who live alone have to go shopping by themselves and often forget to buy the target goods is in their shopping list. This forgetting is because the shopping list is often made with ambiguous expressions compared to the store registered product name. This research proposes a new shopping item forgetting prevention system that can detect the not buying item immediately after purchasing to dealing with the shopping list's ambiguity.

DOI： 10.12792/iciae2021.018

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2021/paper/view/2401

Stereo Matching Based on Features of Image Patch Reviewed

Shi Zhou, He Li, Miaomiao Zhu, Zhen Li, Mitsunori Mizumachi, Lifeng Zhang

Proceedings of the 9th IIAE International Conference on Industrial Applications Engineers 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 18 - 22 2021.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kitakyushu 2021.03.26 - 2020.03.30

Stereo matching is a branch of 3D vision and has a wide range of applications in 3D reconstruction and autonomous driving. Recently, stereo matching methods leverage the information of two full image to calculate disparity map. However, these methods still have difficulties in texture-less regions and occlusion regions, and post-processing is used to improve accuracy. Therefore, there is a large computational cost in the feature extraction and post-processing. In this paper, we propose a stereo matching method based only on features of image patches and predict the disparity of region without occlusion. And post-processing is performed to modify all kind of mismatching based on the correct disparity. Furthermore, we evaluated our proposed method on the Middlebury dataset. The results show that our method performs well in all areas.

DOI： 10.12792/iciae2021.006

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2021/paper/view/2423

Proposal of a System for the Visually Impaired to Identify Store Front Merchandise with no Assistance Reviewed

Tomoyuki Zaizen, Lifeng Zhang

Proceedings of the 9th IIAE International Conference on Industrial Applications Engineers 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 13 - 17 2021.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kitakyushu 2021.03.26 - 2020.03.30

In recent years, the aging of the population in Japan has become a problem. In addition, many elderly people are visually impaired, and the number of visually impaired people is expected to increase in the future. However, the lack of caregivers is also a problem in an aging society, and the problem of not having enough caregivers for the increasing number of visually impaired people is expected to arise in Japan in the future. Due to the shortage of assistants, elderly visually impaired people tend to avoid going out, and their safety confirmation may be delayed. That also becomes a big problem. Therefore, in order to prevent them, it is necessary to have a system that enables the visually impaired to live without nursing care. In this study, we propose a system that enables the visually impaired to buy products without nursing care, which is based on an image processing technique and machine learning.

DOI： 10.12792/iciae2021.005

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2021/paper/view/2399

A Proposal for Creating Syllabic Datasets for Japanese Language Lipreading by Using Machine Learning Reviewed

Rui Kitahara, Lifeng Zhang

Proceedings of the 9th IIAE International Conference on Industrial Applications Engineers 2021 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 8 - 12 2021.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Kitakyushu 2021.03.26 - 2020.03.30

Although lip-reading using image processing and machine learning has been mainly performed at the word level, it has been shown that using LipNet, a network that enables recognition at the sentence level, improves the recognition accuracy over the former method. However, this was the case for English speakers. In this study, the data set was created based on speech scenes containing all 50 Japanese sounds, and the recognition accuracy was evaluated using LipNet.

DOI： 10.12792/iciae2021.004

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2021/paper/view/2397

3D Object Detection Algorithms on Intelligent Driving: A Survey Reviewed

Zhen Li, Miaomiao Zhu, Shi Zhou, Lifeng Zhang

PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL LIFE AND ROBOTICS (AROB 26th 2021) ( International Society of Artificial Life and Robotics ) 1 ( 1 ) 38 - 43 2021.01

Language：English Publishing type：Research paper (international conference proceedings)

Japan Online 2021.01.21 - 2021.01.23

With the rapid development of Artificial Intelligent algorithms on Computer Vision, 2D object detection has greatly succeeded and been applied in various industrial products. In the past several years, the accuracy of 2D object detection has been dramatically improved, even beyond the human eyes' detection ability. However, there is still a limitation of 2D object
detection using for the application of Intelligent Driving. A safe and reliable self-driving car needs to detect a 3D model of the around objects so that an intelligent driving car has a perception ability to real driving situations. This paper systematically surveys the development of 3D object detection methods applied to intelligent driving technology. This paper also analyzes the shortcomings of the existing 3D detection algorithms and the future development direction of 3D detection algorithms on intelligent driving.

Self-supervised Monocular Depth Estimation with Occlusion Mask and Edge Awareness Reviewed

Shi Zhou, Miaomiao Zhu, Zhen Li, Mitsunori Mizumachi, Lifeng Zhang

PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL LIFE AND ROBOTICS (AROB 26th 2021) ( International Society of Artificial Life and Robotics ) 1 ( 1 ) 404 - 408 2021.01

Language：English Publishing type：Research paper (international conference proceedings)

Japan Online 2021.01.21 - 2021.01.23

Depth estimation is one of the basic and important tasks in 3D vision. Recently, many works have been done in selfsupervised depth estimation based on geometric consistency between frames. However, these research works still have difficulties in ill-posed regions, such as occlusion areas and texture-less areas. This work proposes a novel self-supervised monocular depth estimation method based on occlusion mask and edge awareness to overcome these difficulties. The occlusion mask divides the image into two classes, making the training of the network more reasonable. The edge awareness loss function is designed based on the edge obtained by the traditional method, so that the method has strong robustness to various lighting conditions. Furthermore, we evaluated our proposed method on the KITTI dataset. The occlusion mask and edge awareness are both beneficial to find corresponding points in ill-posed regions.detection using for the application of Intelligent Driving. A safe and reliable self-driving car needs to detect a 3D model of the around objects so that an intelligent driving car has a perception ability to real driving situations. This paper systematically surveys the development of 3D object detection methods applied to intelligent driving technology. This paper also analyzes the shortcomings of the existing 3D detection algorithms and the future development direction of 3D detection algorithms on intelligent driving.

Person Re-identification in the Real-World Application Based on Deep Learning Reviewed

Miaomiao Zhu, Shengrong Gong, Zhenjiang Qian, Seiichi Serikawa, and Lifeng Zhang

PROCEEDINGS OF THE TWENTY-SIXTH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL LIFE AND ROBOTICS (AROB 26th 2021) ( International Society of Artificial Life and Robotics ) 1 ( 1 ) 228 - 233 2021.01

Language：English Publishing type：Research paper (international conference proceedings)

Japan Online 2021.01.21 - 2021.01.23

Person re-identification (ReID) aims at retrieving a person of interest across multiple non-overlapping cameras. Because of increasing demand for real-world applications in intelligent video surveillance, person re-identification has become an important task in computer vision, and achieved high performance in recent years. However, the traditional research is mainly
focus on matching cropped pedestrian images between queries and candidates on commonly used datasets, and divided into two steps: pedestrian detection and person re-identification, there is still a big gap with practical applications. Under the premise of model optimization, based on the existing object detection and person re-identification, this paper achieves a one-step search of specific pedestrians in whole images or video sequences in actual application scenario. The experimental results show that our method is effective in commonly used datasets, and has achieved good results in the real-world application, such as finding criminals, cross-camera person tracking and activity analysis.

Proposal of Japanese Syllabary Data Set Construction for Japanese Lip Reading using Machine Learning International journal

Kitahara Rui, Zhang Lifeng

Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2021 ( 0 ) 28 - 29 2021.01

Development of Virtual Marker Type Automatic Tracking Projection Mapping System by Image Processing Reviewed

Masaki Inoue, Lifeng Zhang

Proceedings of International Conference on Technology and Social Science 2020 (ICTSS 2020) 2020.12

Language：English Publishing type：Research paper (international conference proceedings)

日本 Kiryu, Japan 2020.12.02 - 2020.12.04

In recent years, automatic tracking projection mapping that maps moving objects such as people and balls has also become extensive.
As a principle of auto-following projection mapping, using a marker for specifying the position of a projection target is common. The position is estimated by reflecting the infrared rays emitted from the projector by the marker attached to the projection target.
This research has developed a tracking projection mapping system that does not require physical markers but can realize a more flexible image expression.
The system performs follow-up mapping without physical markers by virtualizing markers that estimate the projection target's position, a three-dimensional figure such as a cube or rectangular parallelepiped, by image processing. Specifically, we have realized a target position estimation system that does not require physical markers by accurately detecting the four corners of the projection target by performing corner detection step by step using ROI.

Research on Image Privacy Protection Algorithm Based on Generative Adversarial Network Reviewed International journal

Wu Zhiqiang, Zhang Lejun, Zhang Lifeng, Seiichi Serikawa

2020 2nd International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI) ( IEEE ) 500 - 504 2020.10

Language：English Publishing type：Research paper (international conference proceedings)

China Taiyuan 2020.10.23 - 2020.10.25

In view of the existing privacy protection means, the sensitive areas in the pictures, such as face, text and other parts, are changed to protect privacy, or the objects involving privacy are removed from the picture or video. However, the obvious defect of these methods is that they destroy the practicability of the photos. When the privacy information in the photos is removed, the important information contained in the photos is also removed. In order to solve this problem, this paper introduces the generative adversarial network and proposes an image privacy protection algorithm. This algorithm defines information privacy methods and optimizes limited areas to ensure that information is properly protected. Different image protection schemes are designed to adapt and not adapt to the safe path. In order to meet the needs of privacy protection, we apply the image privacy protection algorithm in the generative adversarial network. Finally, the simulation analysis of the privacy protection algorithm based on the generative adversarial network is carried out. The experimental results show that compared with the encryption algorithm, the privacy protection algorithm based on the generative adversarial network has better performance in the end-to-end delay and encryption speed.

DOI： 10.1109/MLBDBI51377.2020.00105

Other Link： https://ieeexplore.ieee.org/document/9361051

Person Re-identification on Mobile Devices Based on Deep Learning Reviewed

Miaomiao Zhu, Shengrong Gong, Zhenjiang Qian, Lifeng Zhang

Proceedings of the 8th IIAE International Conference on Industrial Applications Engineers 2020 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 253 - 260 2020.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Matsue 2020.03.26 - 2020.03.30

Person Re-identification as an important supplement to face recognition, refers to a network of cameras with non-overlapping vision domains, through the use of computer vision technology to solve the cross-camera and cross-scene pedestrian recognition and retrieval. That is, determine whether there is a specific pedestrian to be detected in the different images or different video sequences. At present, many person re-identification research works mainly carried out through experimental verification and evaluation on large ReID datasets such as Market-1501, DukeMTMC-reID, MSMT17, and CUHK03. In this paper, based on the existing deep-learning person re-identification research, combines with the actual application scenarios, under the premise of analyzing the technical feasibility, we propose a complete process for Person Re-identification based on mobile devices, aims to combine pedestrian detection and person re-identification to perform real-time pedestrian detection and query. In this process, not only the features extracted by pedestrians can be reused, but also the research on person re-identification can be better and effectively applied, such as tracking criminals and searching for missing children.

DOI： 10.12792/iciae2020.044

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2020/paper/view/2351

AI security--The Application of Adversarial Samples in Face Recognition Reviewed

ZhangLe Jun, Wu Zhiqiang, Zhang Lifeng, Seiichi Serikawa

Proceedings of the 8th IIAE International Conference on Industrial Applications Engineers 2020 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 336 - 340 2020.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Matsue 2020.03.26 - 2020.03.30

With the development of economy and the advancement of science and technology, society's requirements for the accuracy of face recognition have gradually increased, and its dependence on face recognition technology has become stronger and stronger. When deploying a neural network in a high-security environment, it is usually easier to ignore the security threat caused by vulnerability. Fully analyze the vulnerability of traditional face recognition technology, and use the generated adversarial samples to design a novel eyeglass patch sample, which can successfully deceive the face recognition system based on convolutional neural network. In addition, the security of artificial intelligence can bring new opportunities for face recognition. Applying artificial intelligence technology to face recognition can effectively improve accuracy. The research purpose of this paper is to analyze the application of adversarial samples in face recognition based on the security of artificial intelligence in order to solve the problems of low security and high vulnerability in traditional face recognition.

DOI： 10.12792/iciae2020.057

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2020/paper/view/2329

Face Recognition with Age, Gender and Emotion Estimations Reviewed

Dongqin Gu, Miaomiao Zhu, Lifeng Zhang, Seiichi Serikawa

Proceedings of the 8th IIAE International Conference on Industrial Applications Engineers 2020 ( The Institute of Industrial Applications Engineers ) 1 ( 1 ) 324 - 329 2020.03

Language：English Publishing type：Research paper (international conference proceedings)

Japan Matsue 2020.03.26 - 2020.03.30

Based on the residual network, this paper proposes a system for face recognition with gender, age and emotion estimations. It can be implemented in different retail industries, helping merchants build their own databases, analyze consumers' shopping preferences with different ages and genders, track users' sentiment, feedback users' experience, and adjust purchase lists and operating modes in a timely manner.

DOI： 10.12792/iciae2020.055

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2020/paper/view/2321

Optimization for greedy non-maximum suppression based on multi-task convolutional neural network Reviewed

Qingqing Hong, Qian Fan, Lifeng Zhang

Journal of the Institute of Industrial Applications Engineers ( The Institute of Industrial Applications Engineers ) 8 ( 1 ) 39 - 45 2020.01

Language：English Publishing type：Research paper (scientific journal)

Non-maximum suppression (NMS) is an essential part of the face detection pipeline based on a convolutional neural network (CNN). The typical approach for NMS used by face detection is a greedy, locally optimal strategy, which is to localize objects from a set of candidate locations. However, NMS still has some shortcomings, such as sometimes the detection box has no relationship with a high classification score, which leads to misjudging face localization during NMS. In this paper, we observed that the NMS implemented on the multi-task convolutional neural network (MTCNN) is a cascaded network and the enhanced NMS based on MTCNN to achieve high performance during face detection and alignment. We employ WIDER FACE as the test dataset to evaluate our proposal. The precision and recall curves are drawn when using three subsets at different thresholds. The result shows that the proposed approach can perform better performance than traditional NMS.

DOI： 10.12792/JIIAE.8.39

Other Link： https://www2.ia-engineers.org/Journal_E/index.php/jiiae/article/view/197

An Application of Multi-Face Recognition Based on Feature Extraction Reviewed

Dongqin Gu, Seiichi Serikawa, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 207 - 211 2019.09

Research for Improving Identification Accuracy of Specific Fish Species with CNN Reviewed

Yuta Shoji, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 190 - 193 2019.09

Preprocessing Method for Training Dataset in Character Recognition using Convolutional Neural Networkbase Reviewed

Akase Taku, Hitoshi Nakao, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 186 - 189 2019.09

Proposal of Character Correction Method using Database Reviewed

Takahiro Fujishima, Ken Kariya, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 178 - 181 2019.09

Development of OCR Mobile Application Including Miss-recognized Proofreading System Using Database Search Algorithm Reviewed

Ken Kariya, Takahiro Fujishima, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 182 - 185 2019.09

Authorship：Corresponding author Language：English Publishing type：Research paper (international conference proceedings)

日本北九州市 2019.09.05 - 2019.09.09

DOI： 10.12792/icisip2019.034

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2194/1419

Development of the System which Recognize of Mark of "Stop" and Judge Stop Status by In-vehicle Camera Reviewed

Ryota Kaneto, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 219 - 223 2019.09

Proposal of Pointing Device for Handicapped Person using Finger Position Detection with Web Camera Reviewed

Masaki Inoue, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 254 - 258 2019.09

Pulse Measurement with Web Camera Reviewed

Kentaro Kajioka, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 250 - 253 2019.09

Optimization for Greedy Non-maximum Suppression based on Multi-task Convolutional Neural Network Reviewed

Hong Qingqing, Fan Qian, Zhang Lifeng

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 243 - 249 2019.09

A Brief Review on Cycle Generative Adversarial Networks Reviewed

Miao Miao Zhu, Shengrong Gong, Zhenjiang Qian, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 235 - 242 2019.09

The Temperature Warning System based on the Renesas MCU Reviewed

Miao Miao Zhu, Shengrong Gong, Zhenjiang Qian, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 230 - 234 2019.09

A Semi-Dense Feature-based VSLAM System Reviewed

Zhen Li, Yuren Du, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 224 - 229 2019.09

Product Discrimination System Using Deep Learning Reviewed

Hitoshi Nakao, Taku Akase, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Intelligent Systems and Image Processings 2019 ( The institute of Industrial Applications Engineers ) 217 - 218 2019.09

A Study on Robot Tracking based on Deep Learning and Monocular Vision Reviewed

Yiyang Chen, Wanpei Chen, Lifeng Zhang

Proceedings of the 7th IIAE International Conference on Industrial Application Engineering 2019 89 - 93 2019.03

Design of Frequency and Phase Measurement System Reviewed

Zhen Li, Lifeng Zhang, Yuren Du

Proceedings of the 7th IIAE International Conference on Industrial Application Engineering 2019 79 - 83 2019.03

A study on robot tracking based on Camshift algorithm Reviewed

Yiyang Chen, Lifeng Zhang

PROCEEDINGS OF THE TWENTY-FOURTH INTERNATIONAL SYMPOSIUM ON ARTIFICIAL LIFE AND ROBOTICS (AROB 24th 2019) 549 - 533 2019.01

A hybrid DCT-CLAHE approach for brightness enhancement of uneven-illumination underwater images Reviewed

Ge M., Hong Q., Zhang L.

ACM International Conference Proceeding Series 123 - 127 2018.12

Image Classification System Not Affected by Background and Text Color Reviewed

Taku Akase, Hitoshi Nakao, Lifeng Zhang

Proceedings of the 6th IIAE International Conference on Industrial Application Engineering 2018 151 - 154 2018.03

Underwater Image Brightness Enhancement based on the DCT Coefficient Model using Genetic Algorithm Reviewed

Meng Ge, Qingqing Hong, Qian Fan, Lifeng Zhang

Proceedings of the 6th IIAE International Conference on Industrial Application Engineering 2018 352 - 355 2018.03

Proposal of Character Recognition Algorithm Using Database Reviewed

Takahiro Fujishima, Ken Kariya, Lifeng Zhang

Proceedings of the 6th IIAE International Conference on Industrial Application Engineering 2018 155 - 158 2018.03

A novel patch matching algorithm for exemplar-based image inpainting Reviewed International journal

Fan Q., Zhang L.

Multimedia Tools and Applications 77 ( 9 ) 11807 - 11821 2018.01

Research on formal design and verification of operating systems Reviewed

Qian Z., Liu Y., Jin Y., Xing X., Zhang M., Gong S., Liu W., Yang W., Tan J., Zhang L.

Communications in Computer and Information Science 857 81 - 88 2018.01

Accuracy Verification of Product Classification System using Deep Learning

Akase Taku, Nakao Hitoshi, Zhang Lifeng

Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2018 ( 0 ) 91 - 92 2018.01

A Garment Detection Method of Iterating Grabcut Based on the most Reliable Seed Reviewed

Nozomi Matsuda, Meng Ge, Qian Fan, Lifeng Zhang

Journal of the Institute of Industrial Applications Engineers 5 ( 2 ) 79 - 85 2017.04

Study of the Finger Detection Technology for the One Camera Touch Panel

Goto Hiroki, Ge Meng, Zhang Lifeng

Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2017 ( 0 ) 67 - 68 2017.01

Reaserch on High-Speed Face Authentication Algorithm for IoT Devices

Shinozaki Naoya, Ge Meng, Serikawa Seiichi, Zhang Lifeng

Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2017 ( 0 ) 71 - 72 2017.01

Research for Equalizing of the Illumination of the Underwater Image Using the Artificial Illumination International journal

Shinto Masato, Hong Qinqin, Ge Meng, Zhang Lifeng

Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2017 ( 0 ) 17 - 18 2017.01

Formation Technique of Code using Pixel Value for the Information Hiding

Kikuta Kazushi, Zhang Lifeng

Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2017 ( 0 ) 73 - 74 2017.01

Exemplar-based image inpainting algorithm using adaptive sample and candidate patch system Reviewed International journal

Qian F., Lifeng Z., Xuelong H.

2015 IEEE 12th International Conference on Electronic Measurement and Instruments, ICEMI 2015 3 1219 - 1223 2016.06

The Study of Detection Method of Echizen Jellyfish Using Images from the Internet International journal

Sugimoto Yudai, Sagara Kazutaka, Zhang Lifeng

Proceedings of IIAE Annual Conference ( The Institute of Industrial Applications Engineers ) 2016 ( 0 ) 56 - 57 2016.01

Identify a specified fish species by the Co-occurrence matrix and adaboost Reviewed

Zhang L., Yamawaki A., Serikawa S.

Studies in Computational Intelligence 569 99 - 112 2015.01

Children Identification Method Based on Clothing Feature

MATSUDA Nozomi, ZHANG Lifeng

Proceedings of the Annual Conference of Biomedical Fuzzy Systems Association ( Biomedical Fuzzy Systems Association ) 28 ( 0 ) 205 - 206 2015.01

Language：Japanese Publishing type：Research paper (scientific journal)

The kindergarten children identification technology is a useful technique for monitoring the existence of child automatically in a short time span. Due to the fact that the infant faces are difficult to be identified, this work proposes a personal identification method using clothing feature. The proposed method extracts clothing regions from images according to the face position. Then it identifies the individual by comparison of clothing feature. The experimental result shows the possibility that the proposed method is able to identify children.

DOI： 10.24466/pacbfsa.28.0_205

CiNii Article

Other Link： https://ci.nii.ac.jp/naid/130007998563

Development of Single Camera Finger Touch Position Detection System Reviewed

Shenjing Chen, Lifeng Zhang, Seiichi Serikawa

Journal of the Institute of Industrial Applications Engineers 2 ( 3 ) 108 - 112 2014.07

An implementation of document image reconstruction system on a smart device using a 1D histogram calibration algorithm Reviewed

2014 2014.01

Real-time visualization system for deep-sea surveying Reviewed

2014 2014.01

Images pre-processing for deep-sea sonar imaging systems Reviewed

Lu H., Li Y., Zhang L., Serikawa S.

Information (Japan) 17 ( 1 ) 145 - 151 2014.01

Language：English Publishing type：Research paper (scientific journal)

In this paper, we describe a novel image preprocessing pipeline for removing underwater sonar image noise, enhancing the structure of sonar images, and fusing the different sonar images, in the curvelet domain. Side-scan sonar acquires high quality imagery of the seafloor with very high spatial resolution but poor locational accuracy. On the other hand, multi-beam sonar obtains high precision position and underwater depth in seafloor points. In order to fully utilize all information of these two types of sonars, it is necessary to fuse the two kinds of sonar data. This paper gives curvelet transform for enhancing the signals or details in different scales separately. It also proposes a new intensity sonar image fusion method, which is based on curvelet transform. The experimental results show that the method can be used in the flat seafloor or the isotropic seabed. Compared with wavelet transform method, this method can get better performance. © 2014 International Information Institute.

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84899681515&origin=inward

Precise corresponding point detection proposal for distance measurement by using a home-use 3D camera Reviewed

Zhang L., Koda T., Yang S., Serikawa S.

Information (Japan) 17 ( 1 ) 125 - 130 2014.01

Multiframe medical images enhancement on dual tree complex wavelet transform domain Reviewed

611 - 614 2013.10

Cross depth image filter-based natural image matting Reviewed

601 - 604 2013.10

Distance measurement with a general 3D camera by using a modified phase only correlation method Reviewed

173 - 177 2013.10

Underwater optical image dehazing using guided trigonometric bilateral filtering Reviewed

2147 - 2150 2013.09

Underwater laser images denoising using bayesian contourlet estimator of bessel K form Reviewed

4 ( 3 ) 533 - 539 2013.06

Fast active contours-based segmentation method for medical image objects detection Reviewed

4 ( 3 ) 677 - 682 2013.06

Improved dark channel dehazing Reviewed

Chen B., Xie Y., Zhang L., Serikawa S.

ICIC Express Letters 7 ( 3 B ) 1037 - 1041 2013.03

A calibration method for partially acquired print document image by web camera Reviewed

Uchimura Y., Zhang L., Kouda T., Lu H., Serikawa S.

ICIC Express Letters 7 ( 3 A ) 861 - 866 2013.03

Proposal of a Flexible Touch Panel Using a Resistive Film("jointly worked") Reviewed

Ryosuke Suzue, Lifeng Zhang

The Proceedings of the 1st International Conference on Industrial Application Engineering 2013 265 - 268 2013.03

Discrimination of Specific Introduced Species of Waterside Used AdaBoost("jointly worked") Reviewed

Yousuke Katayama,Yousuke Uchimura,Lifeng Zhang

The Proceedings of the 1st International Conference on Industrial Application Engineering 2013 261 - 264 2013.03

Method for Acquisition of Camera Document Images' Distorted Gradient("jointly worked") Reviewed

Yingying Wang, Huimin Lu,Jun Cai, Lifeng Zhang

The Proceedings of the 1st International Conference on Industrial Application Engineering 2013 226 - 231 2013.03

Semi-supervised Learning based Dark Channel Dehazing("jointly worked") Reviewed

Bolong Chen, Yong Xie, and Lifeng Zhang

The Proceedings of the 1st International Conference on Industrial Application Engineering 2013 221 - 225 2013.03

The Orthogonal Transform Sign("jointly worked") Reviewed

Lifeng Zhang, Takaharu Koda, Huimin Lu

The Proceedings of the 1st International Conference on Industrial Application Engineering 2013 112 - 118 2013.03

A Proposal For Print Document Acquisition Using Video Camera Equipped Device("jointly worked") Reviewed

Yousuke Uchimura,Yousuke Katayama,Lifeng Zhang

The Proceedings of the 1st International Conference on Industrial Application Engineering 2013 43 - 48 2013.03

Using online attendance management system constructs the function of score evaluation and score search("jointly worked") Reviewed

Qiangxing Yao, Lifeng Zhang

The Proceedings of the 1st International Conference on Industrial Application Engineering 2013 17 - 20 2013.03

Proposal on the Creation of Visual Effects in the Frequency Domain of the Image Reviewed

Lifeng Zhang, Qian Fan

The Japanese Journal of the Institute of Industrial Applications Engineers 1 ( 1 ) 33 - 34 2013.03

A Calibration Method for Partially Acquired Print Document Image by Web Camera("jointly worked") Reviewed

Yousuke Uchimura, Lifeng Zhang,Takaharu Kouda, Huimin Lu, Seiichi Serikawa

ICIC Express Letters 7 ( 3(A) ) 861 - 866 2013.03

Improved Dark Channel Dehazing("joint worked") Reviewed

Bolong Chen, Yong Xie, Lifeng Zhang, Seiichi Serikawa

ICIC Express Letters 7 ( 3(B) ) 1037 - 1041 2013.03

Enhancing underwater image by dehazing and colorization Reviewed

7 ( 7 ) 3470 - 3474 2012.12

Fast level set segmentation method in medical multi-sensor images detection Reviewed

4 ( 23 ) 475 - 482 2012.12

Proposal of alert system for prevention of heat stroke Reviewed

111 - 116 2012.12

Proposal of person position detecting method using pyroelectric sensor Reviewed

121 - 124 2012.12

Robust color image segmentation method based on weighting Fuzzy C-Means Clustering Reviewed

133 - 137 2012.12

Anisotropic Multivariate Shrinkage Function-Based Image Denoising in the Second Generation Curvelet Transform Domain Reviewed

Lifeng Zhang, Yuejie Li, Huimin Lu, Seiichi Serikawa

ICIC Express Letters, Part B: Applications 3 ( 5 ) 1133 - 1138 2012.10

Proposal of A Multi-Sensor Fusion Method for Pan-Sharpening in Sharp Frequency Localized Contourlet Transform Domain Reviewed

Huimin Lu, Lifeng Zhang, Seiichi Serikawa

Disaster Advances 5 ( 4 ) 244 - 253 2012.10

Maximum Local Energy Method for Multispectral Image Fusion in Remote Sensing System Reviewed

Lifeng Zhang, Huimin Lu, Seiichi Serikawa

Disaster Advances 5 ( 4 ) 117 - 120 2012.10

Maximum local energy: An effective approach for multisensor image fusion in beyond wavelet transform domain ("jointly worked") Reviewed

Huimin Lu,Lifeng Zhang, Seiichi Serikawa

Computers & Mathematics with Applications 64 ( 5 ) 996 - 1003 2012.09

Maximun Local Engery based Multifocus Image Fusion In Mirror Extended Curvelet Transform Domain("jointly worked") Reviewed

Lifeng Zhang, Huimin Lu, Yujie Li, Seiichi Serikawa

2012 13th ACIS International Conference on Software engineering, Artifical Intelligence, Networking and Parallel/Distributed Computing 799 - 802 2012.08

Multimodial Medical Image Fusion in Modified Sharp Frequency Localized Contourlet Domain ("jointly worked") Reviewed

Seiichi Serikawa, Huimin Lu, Yujie Li, Lifeng Zhang

2012 13th ACIS International Conference on Software engineering, Artifical Intelligence, Networking and Parallel/Distributed Computing 33 - 37 2012.08

A new method for CT/MR image fusion based on bandelets transform Reviewed

141 LNEE ( VOL. 1 ) 587 - 592 2012.02

Proposal of a touch panel switch with the function of bending and addition "jointly worked" Reviewed

Seiichi Serikawa, Lifeng Zhang

8 - 13 2011.12

An Improved Detection Algorithm Based on Morphology Methods for Blood Cancer Cells Detection (jointly worked) Reviewed

Yujie Li, Huimin Lu, Lifeng Zhang, Yuhki Kitazono, Kohei Miyata, Shota Nakashima, Shiyuan Yang, and Seiichi Serikawa

7 ( 13 ) 4724 - 4731 2011.12

Proposal of intelligence module type robot that can exchange it in seamless Reviewed

975 - 978 2011.12

A Method for 3D Sphere Detection Using One-Dimensional Histogram and Polytope Method("jointly worked") Reviewed

Shota Nakashima, Hiroyuki Nakamoto, Yuhki Kitazono, Lifeng Zhang, Serikawa Seiichi

Applied Mechanics and Materials 103 628 - 632 2011.09

Development of Position Detector with Large Sensing Area Using Frosted Glass Reviewed

Yuhki Kitazono, Kohei Miyata, Shota Nakashima, Lifeng Zhang, Seiichi Serikawa

Applied Mechanics and Materials 103 600 - 605 2011.09

A New Image Segmentation Method Based on Improved Fast Implicit Level Set Scheme in X/γ-Ray Inspection System Reviewed

Yujie LI, Huimin Lu, Lifeng Zhang, Shiyuan Yang, Seiichi Serikawa

Applied Mechanics and Materials 103 705 - 710 2011.09

An Improved Method for CT/MRI Image Fusion on Bandelets Transform Domain Reviewed

Huimin Lu, Shota Nakashima, Yujie LI, Lifeng Zhang, Shiyuan Yang, Seiichi Serikawa

Applied Mechanics and Materials 103 700 - 704 2011.09

Proposal of Fast Implicit Level Set Scheme for Medical Image Segmentation Using the Chan and Vese Model Reviewed

Huimin Lu, Seiichi Serikawa, Yujie Li, Lifeng Zhang, Shiyuan Yang, Xuelong Hu

Applied Mechanics and Materials 103 695 - 699 2011.09

Actual Image Effect Creation According to a Real Lens imaging System Reviewed

Lifeng Zhang, Huimin Lu, Yuhki Kitazono, Seiichi Serikawa

Applied Mechanics and Materials 103 673 - 678 2011.09

A Hybrid Method of Information Embedding for Digital Watermark Reviewed

Lifeng Zhang, Yujie LI, Shota Nakashima, Seiichi Serikawa

Applied Mechanics and Materials 103 667 - 672 2011.09

Color Image Segmentation Using Fast Density-based Clustering Method "jointly worked" Reviewed

Yujie Li, Huimin Lu, Lifeng Zhang, Shiyuan Yang and Seiichi Serikawa,

Future Communication, Computing, Control and Management, Lecture Notes in Electrical Engineering 141 ( 1 ) 593 - 598 2011.09

A New Method for CT/MR Image Fusion Based on Bandelets Transform Domain "jointly worked" Reviewed

2) Huimin Lu, Yujie Li, Lifeng Zhang, Shiyuan Yang, and Seiichi Serikawa

Future Communication, Computing, Control and Management, Lecture Notes in Electrical Engineering 141 ( 1 ) 587 - 592 2011.09

Proposal for a new concept for a robot in which the constructing module can be exchanged seamlessly ("jointly worked") Reviewed

Shunta Takahashi, Kohei Miyata, Yuhki Kitazono, Lifeng Zhang, Seiichi Serikawa

Artif Life and Robotics 16 ( 2 ) 165 - 168 2011.09

Proposal of Method to Extract 3D Sphere using One-Dimensional Histogram"jointly worked" Reviewed

Hiroyoki NAKAMOTO, yukhi KITAZONO, Lifeng ZHANG, Seiichi SERIKAWA,Shota NAKASHIMA

The 3rd International Conference on Precision Instrumentation and Measurement, CPIM2011 47 - 47 2011.07

Proposasl of Optical Position Sensor with Large Area "jointly worked" Reviewed

Yuhki Kitazono,Hohei Miyata, Shota Nakashima, Lifeng Zhang, Seiichi Serikawa

The 3rd International Conference on Precision Instrumentation and Measurement, CPIM2011 44 - 44 2011.07

Digital image filtering effect creation according to a real lens imaging system"jointly worked" Reviewed

Zhang Lifeng, Lu Huimin, Yuhki Kitazono, Seiichi Serikawa

The 3rd International Conference on Precision Instrumentation and Measurement, CPIM2011 2011.07

Image segmentation based on improved fast implicit level set scheme in X/γ-ray inspection system "jointly worked" Reviewed

Li Yujie, Lu Huimin, Zhang Lifeng, Yang Shiyuan, Seiichi Serikawa

The 3rd International Conference on Precision Instrumentation and Measurement, CPIM2011 2011.07

An improved method for CT/MRI image fusion based on bandelets transform "jointly worked" Reviewed

Huimin Lu, Shota Nakashima, Yujie Li, Lifeng Zhang, Shaherca Hossain, Shiyuan Yang, Seiichi Serikawa

The 3rd International Conference on Precision Instrumentation and Measurement, CPIM2011 2011.07

An Automatic Image Segmentation Algorithm Based on Weighting Fuzzy C-Means Clustering "jointly worked" Reviewed

Yujie Li, Huimin Lu, Lifeng Zhang, Junwu Zhu, Shiyuan Yang, Xiaobin Zhang, Xuelong Hu, Yun Li, Bin Li and Seiichi Serikawa

2011 International Conference on Networking, VLSI and Signal Processing 182 24 - 29 2011.05

A New Type of Using Morphology Methods to Detect Blood Cancer Cells "jointly worked" Reviewed

Yujie Li, Huimin Lu, Lifeng Zhang, Shiyuan Yang and Seiichi Serikawa,

2011 International Conference on Networking, VLSI and Signal Processing 182 16 - 23 2011.05

Local Energy based Image Fusion in Sharp Frequency Localized Contourlet Transform Reviewed

Huimin Lu,Xuelong Hu,Lifeng Zhang,Shiyuan Yang,Seiichi Serikawa

Journal of Computational Information Systems 6 ( 12 ) 3997 - 4005 2010.12

A numeric reading system for digital meter without I/O interface Reviewed

Shota Nakashima,Yuki Kitamoto,Huimin Lu,Yuhki Kitazono,Lifeng Zhang,and Seiichi Serikawa

Journal of Computational Information Systems 6 ( 14 ) 4657 - 4664 2010.12

An Improved Large Area-Type Optical Sensor Using Frosted Glass Reviewed

Yuhki Kitazono,Shahera Hossain,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

IEEE Sensors 2010 Conference ( A2P-L7 ) 504 - 507 2010.11

Proposal of 3 Dimension Imaginary Space Touch Panel Using Ultrasonic Sensors Reviewed

Ryo Yasunaka,Yuhki Kitazono,Shota Nakashima,Lifeng Zhang, Seiichi Serikawa

IEEE Sensors 2010 Conference ( B2P-G5 ) 1346 - 1349 2010.11

Local Energy based Multi-focus Image Fusion Method on Curvelet Transforms ("jointed worked") Reviewed

Huimin Lu,Yujie Li,Yuhki Kitazono,Yang Shiyuan,Lifeng Zhang,Seiichi Serikawa

10th International Symposium on Communications and Information Technologies 2010 ( 11 ) 1154 - 1157 2010.10

Auto Seal Authentication System using a Handy Image Capture Device("jointed worked") Reviewed

Lifeng Zhang,Hiroshi Kondo,Seiichi Serikawa

10th International Symposium on Communications and Information Technologies 2010 ( 94 ) 545 - 549 2010.10

Proposal of an Optical Linear Sensor Using One-Side Frosted Glass Reviewed

Yuhki Kitazono,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

Applied Mechanics and Materials (Trans Tech Publications) 36 370 - 375 2010.10

Proposal of Driver Symbol Mark Detection using One-Dimensional Histogram Figure Extraction Method Reviewed

Yue Liu,Yuhki Kitazono,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

Applied Mechanics and Materials (Trans Tech Publications) 36 376 - 380 2010.10

Local Energy based Multi focus Image fusion in Beyond Wavelets Transform Reviewed

Huimin Lu,Xuelong Hu,Shota Nakashima,Lifeng Zhang,Shiyuan Yang,and Seiichi Serikawa

International Workshop on Image Analysis 21 - 25 2010.08

Face Identification Using Facial Expression Reviewed

Lifeng Zhang,Yu Zhang,Shota Nakashima,Huimin Lu,Xuelong Hu,and Seiichi Serikawa

Proceedings of the third International Workshop on Image Analysis 66 - 73 2010.08

Local Energy and Sum Modified Laplacian-based Image Fusion Method in Sharp Frequency Localized Contourlet Transform Domain Reviewed

Huimin Lu,Seiichi Serikawa,Xuelong Hu,Lifeng Zhang,Shota Nakashima,and Shiyuan Yang

2010 International Colloquium on Computing, Communication, Control, and Management 1 285 - 289 2010.08

Proposal of a strong numeric recognition system that independent on the model of digital measuring instrument Reviewed

Shota Nakashima,Yuki Kitamoto,Huimin Lu,Lifeng Zhang,and Seiichi Serikawa

2010 International Colloquium on Computing, Communication, Control, and Management 1 399 - 402 2010.08

Development of a wireless remote controller system using optical sensors with large area consisting of frosted glass Reviewed

130 ( 7 ) 2010.08

A Method for Infrared Image Segment based on Sharp Frequency Localized Contourlet Transform and Morphology Reviewed

Huimin Lu,Lifeng Zhang,Min Zhang,Xuelong Hu,and Seiichi Serikawa

2010 International Conference on Intelligent Control and Information Processing 2 79 - 82 2010.08

Proposal of Symbol Mark Detection using One-Dimensional Histogram and Polytope Figure Extraction Method Reviewed

Yue Liu,Yuhki Kitazono,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

2010 International Conference on Intelligent Control and Information Processing 2 317 - 320 2010.08

A Proposal of Face Identification using Non-orthogonal Transform Sign Reviewed

Lifeng Zhang, Hiroshi Kondo, Seiichi Serikawa

2010 International Conference on Intelligent Control and Information Processing 2 308 - 312 2010.08

すりガラスを用いた大面積光センサによるリモコンシステムの開発 Reviewed

北園優希,中島翔太,張力峰,芹川聖一

電気学会論文誌E 130 ( 7 ) 300 - 309 2010.07

Language：Japanese Publishing type：Research paper (other academic)

磨りガラスに入射する光の減衰特性により、正方形の４つ角に小型の光センサを設置し、入射光の到達強度により、照射位置を割り出す。また、多種の外部ノイズによる影響を修正するため、S−systemによる関す発見を行い、計算値の修正を行う。実験結果から、想定した用途には順分な精度を有することが分かった。

A New Type of Multi-focus Image Fusion Method Based on Curvelet Transforms Reviewed

Xuelong Hu,Huimin Lu,Lifeng Zhang,Seiichi Serikawa

2010 International Conference on Electrical and Control Engineering 1 172 - 175 2010.06

Innovating Sign Selection for Face Identification using DCT Sign Reviewed

Zhang Lifeng,Hiroshi Kondo

INFORMATION 13 ( 3(B) ) 1027 - 1038 2010.05

A New Seal Authentication Reviewed

Zhang Lifeng,Hiramatsu Kazushige,Hiroshi Kondo

INFORMATION 13 ( 3(B) ) 1019 - 1026 2010.05

Proposal of Driver Symbol Mark Detection using One-Dimensional Histogram Figure Extraction Method Reviewed

Yue Liu,Yuhki Kitazono,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

International Conference on Precision Instrumentation and Measurement 2010 ( CPIM2010_A013 ) 2010.03

Development of a Linear Sensor Using Frosted Glass Reviewed

Yuhki Kitazono,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

International Conference on Precision Instrumentation and Measurement 2010 ( CPIM2010_A012 ) 2010.03

Development of privacy-preserving sensor for person detection Reviewed

Shota Nakashima,Yuhki Kitazono,Lifeng Zhang,and Seiichi Serikawa

Procedia - Social and Behavioral Sciences (Elsevier) 2 ( 1 ) 213 - 217 2010.03

Proposal of optical sensor with large area using frosted glass for universal remote controller Reviewed

Yuhki Kitazono,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

Procedia - Social and Behavioral Sciences (Elsevier) 2 ( 1 ) 179 - 185 2010.03

Proposal of system for detection of dangerous state in epilepsy fit using acceleration sensors Reviewed

Daisuke Baba,Yuhki Kitazono,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

Procedia - Social and Behavioral Sciences (Elsevier) 2 ( 1 ) 198 - 203 2010.03

Proposal of intelligence module type robot that can exchange it in seamless Reviewed

Shunta Takahashi,Kohei Miyata,Yuhki Kitazono,Lifeng Zhang,and Seiichi Serikawa

The Sixteenth International Symposium on Artificial Life and Robotics ( GS20-4 ) 975 - 978 2010.01

Proposal of Sign Selection for Face Identification using DCT Sign Reviewed

Zhang Lifeng,Kondo Hiroshi

Proc. of 5th International Conference on Information 212 - 215 2009.11

Seal Authentication Reviewed

Zhang Lifeng,Hiramatsy Kazushige,Kondo Hiroshi

Proc. of 5th International Conference on Information 216 - 219 2009.11

Sensing System for Estimation of Person's Position Using Rod Lens and Line Sensor Reviewed

Shota Nakashima,Yuhki Kitazono,Lifeng Zhang,and Seiichi Serikawa

The 10th International Conference on Computers, Communications and Systems A1-02 2009.11

Development of Dangerous State Detector for Convulsion Fit Reviewed

Daisuke Baba,Yuhki Kitazono,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

The 10th International Conference on Computers, Communications and Systems A2-02 2009.11

Proposal of Optical Sensor with Large Area Using Frosted Glass for Universal Remote Controller Reviewed

Yuhki Kitazono,Shota Nakashima,Lifeng Zhang,and Seiichi Serikawa

International Conference on Security Camera Network, Privacy Protection and Community Safety 2009 SPC2009_A023 2009.10

Development of privacy-preserving sensor for person detection Reviewed

Shota Nakashima,Yuhki Kitazono,Lifeng Zhang, Seiichi Serikawa

International Conference on Security Camera Network, Privacy Protection and Community Safety 2009 SPC2009_A020 2009.10

Proposal of easily operated remote control using a WBE camera Reviewed

Yuhki Kitazono,Kazuyuki Ishida,Lifeng Zhang,Seiichi Serikawa

SCIS & ISIS 2008 FR-4C ( 3 ) 2008.09

Compatible Image Compression with Optimal Interpolation Reviewed

Lifeng Zhang,Tomoya Kawamoto,Masaki Tamura,Hirosi Kondo

The International Conference on Electrical Engineering 2008 (ICEE2008) ( p-162 ) 5 - 5 2008.07

New Approach for Face Identification Reviewed

Lifeng Zhang,Hirosi Kondo,Keisuke Korekoda

The International Conference on Electrical Engineering 2008 (ICEE2008) ( 0-206 ) 5 - 5 2008.07

Compatible Image Compression Reviewed

Lifeng Zhang,Shinosuke Ohta,Hiroshi Kondo

The 23rd International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2008) ( p2-55 ) 1605 - 1608 2008.07

Candidate narrowing for Face Identification Using Facial Expression Reviewed

Lifeng Zhang,Lin Zhao,Keisuke Korekoda,Hiroshi Kondo

The 23rd International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC 2008) ( p1-59 ) 1237 - 1240 2008.07

The nature of signs in Real Orthogonal Transform Reviewed

Lifeng ZHANG,Zhimei YANG,Takaharu KODA,and Hiroshi KONDO

Proc. Of the 4th Conference on New Exploratory Technologies (NEXT 2007) 1 ( Ro-1 ) 95 - 98 2007.10

Sign-only Synthesis Reviewed

Hiroshi Kondo,Zhimei Yang,Takaharu Koda,Lifeng Zhang

INFORMATION 10 ( 1 ) 101 - 110 2007.01

Face authentication using Orthogonal Transform signs Reviewed

L.ZHANG,Y.ZHIMEI,T.KODA,H.KONDO

International Symposium on Communications And Information Technologies 2006 1 ( 1 ) 941 - 944 2006.10

Face Identification Using Facial Expression Reviewed

L.ZHANG,K.KOREKODA,Y.ZHIMEI,T.KODA,H.KONDO

International Symposium on Communications And Information Technologies 2006 531 - 536 2006.10

Sign-only Synthesis Reviewed

H.KONDO, Z.YANG, T.KOUDA, L.ZHANG

Proc. of 4th International Conference on Information - MFCSIT'06 134 - 138 2006.08

NEW ADAPTIVE TECHNIQUE FOR BINARY SIGNAL COMPRESSION : APPLICATION OF HADAMARD SIGNS Reviewed

Zhimei Yang,Takaharu Koda,Lifeng Zhang,Hiroshi Kondo

International Workshop on Advaced Image Technology 1 ( 1 ) 225 - 25229 2006.01

Binary Signal Compression using DCT Signs Reviewed

H.KONDO,S.KUNIFUSA,Z.YANG,T.KODA,L.ZHANG

Proc. of ICARA 2004 1 ( PS-1 ) 240 - 243 2004.12

Human Moving Detection by Frequency Analysis Using Video Signal Reviewed

Lifeng ZHANG,Hiroshi KONDO

Proc. of ISCIT2004 1 427 - 430 2004.10

DWT Digital Image Compression with no Indication Map Reviewed

Hirohsi KONDO,Hiroki KOU,Takaharu KOUDA,Lifeng ZHANG

INFORMATION 6 ( 4 ) 485 - 490 2003.10

DWT Image Compression For Mobile Communication Reviewed

L.ZHANG,T.KOUDA,H.KONDO,T.SHIMOMURA

DSP workshop in MVS(Mobile and Vehiclar System) 1 18 - 18 2003.04

High Picture Quality Image Compression Technique for Mobile Communication Reviewed

H.KONDO,T.ISHIKAWA,T.KOUDA,L.ZHANG

IEEE ICIT'02 2 ( E4-2 ) 754 - 758 2002.12

Simple Image Compression for Mobile Communication Reviewed

H.KONDO,H.KOU,T.KOUDA,L.ZHANG

Proc. of ISPACS 2002 1 ( B2-2 ) 105 - 109 2002.11

Image Compression using DWT for Mobile system Reviewed

Hiroshi KONDO,Takuya ISHIKAWA,Takaharu KOUDA,Lifeng ZHANG

proc. of KES2002 1 ( 20 ) 562 - 566 2002.09

DWT Digital Image Compression with No Indication MAP Reviewed

Hiroshi KONDO,Hiroki KOU,Takaharu KOUDA,Lifeng ZHANG

Proc. of Information 2002 266 - 268 2002.07

Image Restoration using Spatially Variant Innovating Inverse Filter with Edge Sharpening Reviewed

Lifeng ZHANG. Hiroshi KONDO

The Institute of Image Information and Television Engineers 56 ( 5 ) '815 - 825 2002.05

Pneumoconiosis Analysis in Chest Radiographs using Neural Network Reviewed

Lifeng ZHANG,Takaharu KOUDA,Hiroshi KONDO

INFORMATION 5 ( 1 ) 117 - 124 2002.01

THE UTILITY OF WAVELET MOSAIC PATTERN FOR NEURAL NETWORK HUMAN-FACE RECONGNITION Reviewed

Hiroshi KONDO,Kazuaki SHIBATA,Lifeng ZHANG

2000 IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS 2000) D8-4-3 1804 - 1809 2000.12

Rounded Opacity Detection in Chest Pneumoconiosis Radiographs using Neural Network Reviewed

Lifeng ZHANG,Takaharu KODA,Hiroshi KONDO

Proceedings of the First International Conference on Information 211 - 212 2000.10

Computer Aided Diagnosis for Pneumoconiosis Radiographs' Using Neural Network Reviewed

Hiroshi KONDO,Lifeng ZHANG,Takaharu KODA

Proc. Of Int. Archives of Photogrammetry and Remote Sensing 23 ( B ) 453 - 459 2000.07

Neural Network Human-Face Recognition Using Wavelet Mosaic Pattern Reviewed

Lifeng ZHANG,Hiroshi KONDO

Proceedings of fifth International Symposium on Artificial Life and Robotics 2 523 - 529 2000.01

Image Compression using Sub-blocks based on The Image Reviewed

Hiroshi KONDO,Takuya SATO,Lifeng ZHANG

Proceedings of IASTED International Conference Signal and Image Processing ( 292-151 ) 256 - 260 1999.10

Image Edge Sharpening with Phase Correction Reviewed

Hiroshi KONDO,Lifeng ZHANG

IEICE E82-D ( 8 ) 1200 - 1209 1999.08

New Approach for Image Enhancement Reviewed

Hiroshi KONDO,Lifeng ZHANG,Agus SUHARNO

The Fifth International Conference on Control,Automation,Robotics and Vision 1 809 - 813 1998.12

The Effect of the Observation Fourier Sign Correction for Image Sharpening Reviewed

Hiroshi KONDO,Lifeng ZHANG

ICSP '98. 1998 Fourth International Conference on Signal Processing Proceedings, 1998. 2 861 - 864 1998.10

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Papers - ZHANG Lifeng