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

DOI： 10.12792/iciae2023.022

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

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

DOI： 10.12792/iciae2023.035

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

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

DOI： 10.12792/iciae2023.026

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

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

DOI： 10.12792/iciae2023.025

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

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

DOI： 10.12792/iciae2023.024

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

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

DOI： 10.12792/iciae2023.023

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

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

DOI： 10.1016/j.jallcom.2022.168391

Scopus

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Authorship：Last author   Language：Japanese   Publishing type：Research paper (conference, symposium, etc.)

DOI： 10.12792/iiae2023.018

CiNii Research

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

DOI： 10.1039/d2ay01271e

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85140414844&origin=inward

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

DOI： 10.12792/icisip2022.026

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

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

DOI： 10.12792/icisip2022.020

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

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/icisip2022.019

DOI： 10.12792/icisip2022.019

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

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

DOI： 10.12792/icisip2022.024

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

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

DOI： 10.12792/icisip2022.023

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

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

DOI： 10.12792/icisip2022.025

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

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

DOI： 10.12792/iciae2022.039

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

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

DOI： 10.12792/iciae2022.028

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

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

DOI： 10.12792/iciae2022.023

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

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

DOI： 10.1007/s10015-021-00711-0

Scopus

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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.

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.

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.

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.

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.

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.

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.

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

DOI： 10.1007/s10015-022-00766-7

Scopus

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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

DOI： 10.1007/s10015-021-00711-0

Other Link： https://link.springer.com/article/10.1007/s10015-021-00711-0

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

DOI： 10.1007/s10015-021-00689-9

Kyutacar

Scopus

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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

DOI： 10.12792/icisip2021.004

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

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

DOI： 10.12792/icisip2021.028

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

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

DOI： 10.12792/icisip2021.030

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

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

DOI： 10.1007/s10015-021-00685-z

Kyutacar

Scopus

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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

Other Link： https://link.springer.com/article/10.1007%2Fs10015-021-00685-z

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

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

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

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

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

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

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

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.

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.

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.

Authorship：Last author   Language：Japanese   Publishing type：Research paper (conference, symposium, etc.)

DOI： 10.12792/iiae2021.017

CiNii Article

CiNii Research

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.

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

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

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

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

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

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

日本   北九州市   2019.09.05  -  2019.09.09

DOI： 10.12792/icisip2019.040

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2157

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/icisip2019.036

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2227

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/icisip2019.035

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2214

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/icisip2019.033

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2191

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

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/icisip2019.043

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2230

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

日本   北九州市   2019.09.05  -  2019.09.09

DOI： 10.12792/icisip2019.049

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2229

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

日本   北九州市   2019.09.05  -  2019.09.09

DOI： 10.12792/icisip2019.048

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2226

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

日本   北九州市   2019.09.05  -  2019.09.09

DOI： 10.12792/icisip2019.047

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2182

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

日本   北九州市   2019.09.05  -  2019.09.09

DOI： 10.12792/icisip2019.046

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2163

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/icisip2019.045

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2162

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

日本   北九州市   2019.09.05  -  2019.09.09

DOI： 10.12792/icisip2019.044

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2154

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

日本   北九州市   2019.09.05  -  2019.09.09

DOI： 10.12792/icisip2019.042

Other Link： https://www2.ia-engineers.org/conference/index.php/icisip/icisip2019/paper/view/2220

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

Japan   Kitakyushu   2019.03.26  -  2019.03.30

DOI： 10.12792/iciae2019.019

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

Japan   Kitakyushu   2019.03.26  -  2019.03.30

DOI： 10.12792/iciae2019.017

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

Japan   Beppu   2019.01.23  -  2019.01.25

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

China   HongKong   2018.12.29  -  2018.12.31

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

DOI： 10.1145/3301506.3301539

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85064526495&origin=inward

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

Japan   Okinawa   2018.03.27  -  2018.03.31

DOI： 10.12792/iciae2018.031

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2018/paper/view/1756

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

Japan   Okinawa   2018.03.27  -  2018.03.31

DOI： 10.12792/iciae2018.067

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2018/paper/view/1730

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

Japan   Okinawa   2018.03.27  -  2018.03.31

DOI： 10.12792/iciae2018.032

Other Link： https://www2.ia-engineers.org/conference/index.php/iciae/iciae2018/paper/view/1790

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

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85056096393&origin=inward

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

DOI： 10.1007/978-981-13-1026-3_6

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85050288809&origin=inward

Authorship：Last author   Language：Japanese   Publishing type：Research paper (other academic)

DOI： 10.12792/iiae2018.047

CiNii Article

CiNii Research

Other Link： https://ci.nii.ac.jp/naid/130007542659

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

DOI： 10.12792/JIIAE.5.79

Other Link： https://www2.ia-engineers.org/Journal_E/index.php/jiiae/article/view/129

Authorship：Last author   Language：Japanese   Publishing type：Research paper (other academic)

DOI： 10.12792/iiae2017.035

CiNii Article

CiNii Research

Other Link： https://ci.nii.ac.jp/naid/130006688874

Authorship：Last author   Language：Japanese   Publishing type：Research paper (other academic)

DOI： 10.12792/iiae2017.037

CiNii Article

CiNii Research

Other Link： https://ci.nii.ac.jp/naid/130006688871

Authorship：Last author   Language：Japanese   Publishing type：Research paper (conference, symposium, etc.)

DOI： 10.12792/iiae2017.038

CiNii Article

CiNii Research

Authorship：Last author   Language：Japanese   Publishing type：Research paper (conference, symposium, etc.)

DOI： 10.12792/iiae2017.010

CiNii Article

CiNii Research

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

DOI： 10.1109/ICEMI.2015.7494492

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84978221097&origin=inward

Authorship：Last author   Language：Japanese   Publishing type：Research paper (other academic)

DOI： 10.12792/iiae2016.030

CiNii Article

CiNii Research

Other Link： https://ci.nii.ac.jp/naid/130006688917

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

DOI： 10.1007/978-3-319-10389-1_8

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84921373243&origin=inward

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

<p><i>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. </i></p>

DOI： 10.24466/pacbfsa.28.0_205

CiNii Article

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

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

DOI： 10.12792/JIIAE.2.108

Kyutacar

Other Link： https://www2.ia-engineers.org/Journal_E/index.php/jiiae/article/view/39

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

DOI： 10.1155/2014/437071

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84902169841&origin=inward

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

DOI： 10.1155/2014/313452

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84903625143&origin=inward

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

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

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84899677353&origin=inward

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

DOI： 10.1109/SNPD.2013.72

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84886074968&origin=inward

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

DOI： 10.1109/SNPD.2013.42

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84885964616&origin=inward

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

DOI： 10.1109/SNPD.2013.101

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84886044272&origin=inward

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

DOI： 10.1109/ISCAS.2013.6572299

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84883408571&origin=inward

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

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84874870824&origin=inward

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

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84874850703&origin=inward

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

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84875338789&origin=inward

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

Scopus

Other Link： https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84875311938&origin=inward

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

Japan   Kitakyushu   2013.03.27  -  2013.03.28

Other Link： https://www2.ia-engineers.org/iciae/index.php/iciae/iciae2013/paper/view/36

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

Japan   Kitakyushu   2013.03.27  -  2013.03.28

DOI： 10.12792/iciae2013.051

Other Link： https://www2.ia-engineers.org/iciae/index.php/iciae/iciae2013/paper/view/61

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

Japan   Kitakyushu   2013.03.27  -  2013.03.28

DOI： 10.12792/iciae2013.044

Other Link： https://www2.ia-engineers.org/iciae/index.php/iciae/iciae2013/paper/view/11

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

Japan   Kitakyushu   2013.03.27  -  2013.03.28

DOI： 10.12792/iciae2013.043

Other Link： https://www2.ia-engineers.org/iciae/index.php/iciae/iciae2013/paper/view/39

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

Japan   Kitakyushu   2013.03.27  -  2013.03.28

DOI： 10.12792/iciae2013.023

Other Link： https://www2.ia-engineers.org/iciae/index.php/iciae/iciae2013/paper/view/31

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

Japan   Kitakyushu   2013.03.27  -  2013.03.28

DOI： 10.12792/iciae2013.009

Other Link： https://www2.ia-engineers.org/iciae/index.php/iciae/iciae2013/paper/view/11

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

Japan   Kitakyushu   2013.03.27  -  2013.03.28

DOI： 10.12792/iciae2013.004

Other Link： https://www2.ia-engineers.org/iciae/index.php/iciae/iciae2013/paper/view/50

Authorship：Corresponding author   Language：Japanese   Publishing type：Research paper (scientific journal)

DOI： 10.12792/jjiiae.001.01.005

Other Link： https://www2.ia-engineers.org/Journal_J/index.php/jjiiae/article/view/v001.n01.07

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

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

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

DOI： 10.1109/SII.2012.6426961

Scopus

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Scopus

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

DOI： 10.4156/ijact.vol4.issue23.56

Scopus

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

DOI： 10.1109/SII.2012.6426939

Scopus

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

DOI： 10.1109/SII.2012.6427307

Scopus

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

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

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

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

DOI： 10.1016/j.camwa.2012.03.017

Scopus

Other Link： http://www.sciencedirect.com/science/article/pii/S0898122112002222

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

Japan   Kyoto   2012.08.08  -  2012.08.10

DOI： 10.1109/SNPD.2012.16

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

Japan   Kyoto   2012.08.08  -  2012.08.10

DOI： 10.1109/SNPD.2012.17

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

DOI： 10.1007/978-3-642-27311-7_78

Scopus

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

INDONESIA   Bandung   2011.11.08  -  2011.11.12

DOI： 10.1109/ICICI-BME.2011.6108580

Scopus

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

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

Scopus

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

DOI： 10.4028/www.scientific.net/AMM.103.628

Scopus

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

DOI： 10.4028/www.scientific.net/AMM.103.600

Scopus

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

DOI： 10.4028/www.scientific.net/AMM.103.705

Scopus

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

DOI： 10.4028/www.scientific.net/AMM.103.700

Scopus

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

DOI： 10.4028/www.scientific.net/AMM.103.695

Scopus

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

DOI： 10.4028/www.scientific.net/AMM.103.673

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

DOI： 10.4028/www.scientific.net/AMM.103.667

Scopus

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

China   Hong kong   2011.09.18  -  2011.09.18

DOI： 10.1007/978-3-642-27311-7_79

Scopus

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

China   Hong kong   2011.09.18  -  2011.09.18

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

DOI： 10.1007/s10015-011-0910-3

Scopus

Other Link： http://www.springerlink.com/content/90554715x05j563p/fulltext.pdf

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

China   Xiangtan   2011.07.18  -  2011.07.20

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

China   Xiangtan   2011.07.18  -  2011.07.20

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

China   xiangtan   2011.07.18  -  2011.07.20

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

China   Xiangtan   2011.07.18  -  2011.07.20

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

China   Xiangtan   2011.07.18  -  2011.07.20

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

Thailand   Bangkok   2011.05.27  -  2011.05.28

DOI： 10.1007/978-3-642-29148-7-5

Scopus

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

Thailand   Bangkok   2011.05.27  -  2011.05.28

DOI： 10.1007/978-3-642-29148-7-4

Scopus

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

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

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

U.S.A.   Hawaii   2010.11.01  -  2010.11.04

DOI： 10.1109/ICSENS.2010.5690145

Scopus

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

U.S.A.   Hawaii   2010.11.01  -  2010.11.04

DOI： 10.1109/ICSENS.2010.5690554

Scopus

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

Tokyo   2010.10.26  -  2010.10.29

DOI： 10.1109/ISCIT.2010.5665164

Scopus

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

Japan   Tokyo   2010.10.26  -  2010.10.29

DOI： 10.1109/ISCIT.2010.5665049

Scopus

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

DOI： 10.4028/www.scientific.net/AMM.36.370

Scopus

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

DOI： 10.4028/www.scientific.net/AMM.36.376

Scopus

Other Link： http://www.scientific.net/AMM.36.376

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

France   nimes   2010.08.24  -  2010.08.27

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

France   nimes   2010.08.24  -  2010.08.27

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

China   YangZhou   2010.08.19  -  2010.08.22

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

China   ＹａｎｇＺｈｏｕ   2010.08.19  -  2010.08.22

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

DOI： 10.1541/ieejsmas.130.300

Scopus

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

China   Dalian   2010.08.13  -  2010.08.15

DOI： 10.1109/ICICIP.2010.5564346

Scopus

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

China   Dalian   2010.08.13  -  2010.08.15

DOI： 10.1109/ICICIP.2010.5564350

Scopus

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

China   Dalian   2010.08.13  -  2010.08.15

DOI： 10.1109/ICICIP.2010.5564335

Scopus

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。

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

China   Wuhan   2010.06.25  -  2010.06.27

DOI： 10.1109/iCECE.2010.49

Scopus

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

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

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

2010.03.18  -  2010.03.20

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

2010.03.18  -  2010.03.20

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

DOI： 10.1016/j.sbspro.2010.01.038

Scopus

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

DOI： 10.1016/j.sbspro.2010.01.032

Scopus

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

DOI： 10.1016/j.sbspro.2010.01.035

Scopus

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

大分   2010.01.27  -  2010.01.29

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

京都   2009.11.06  -  2009.11.09

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

京都   2009.11.06  -  2009.11.09

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

Korea   2009.11.05  -  2009.11.07

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

Korea   2009.11.05  -  2009.11.07

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

2009.10.28  -  2009.10.30

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

2009.10.28  -  2009.10.30

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

nagoya   2008.09.18  -  2008.09.21

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

okinawa   2008.07.06  -  2008.07.10

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

Japan   okinawa   2008.07.06  -  2008.07.10

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

Shimonoseki   2008.07.06  -  2008.07.09

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

Shimonoseki   2008.07.06  -  2008.07.09

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

Korea   2007.10.25  -  2007.10.27

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

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

Thailand   Bangkok   2006.10.18  -  2006.10.20

DOI： 10.1109/ISCIT.2006.339915

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

Thailand   bangkok   2006.10.18  -  2006.10.20

DOI： 10.1109/ISCIT.2006.340006

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

Ireland   2006.08  -  2006.08

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

Naha   2006.01.09  -  2006.01.10

Other Link： http://ci.nii.ac.jp/naid/110004078905

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

ニュージーランド   Palmerston North   2004.12.13  -  2004.12.15

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

札幌   2004.10.26  -  2004.10.29

DOI： 10.1109/ISCIT.2004.1412881

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

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

名古屋   2003.04.03  -  2003.04.04

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

Tailand   Bangkok   2002.12.11  -  2002.12.14

DOI： 10.1109/ICIT.2002.1189261

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

台湾   Kaohsing   2002.11.21  -  2002.11.24

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

イタリア   Crema   2002.09.16  -  2002.09.18

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

中国   北京   2002.07.24  -  2002.07.27

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

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

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

アメリカ   ハワイ   2000.12.05  -  2000.12.08

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

日本   福岡   2000.10.16  -  2000.10.19

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

オランダ   Amsterdam   2000.07.16  -  2000.07.22

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

大分   2000.01.26  -  2000.01.28

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

バハマ   Nassau   1999.10.18  -  1999.10.21

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

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

シンガポール   シンガポール   1998.12.09  -  1998.12.11

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

中国   北京   1998.10.12  -  1998.10.16

DOI： 10.1109/ICOSP.1998.770747

Event date： 2011.09.26   Language：Japanese  

そこで本研究では,ペルチェ素子を用いた体感温度調節装置を提案する。本装置はペルチェ素子で冷却した水を循環させながら人間の皮膚に触れることで皮膚の表面温度を下げ,人間の体感温度を調節する。本装置の構成は,安価で実現可能である。さらにペルチェ素子を使用することにより,消費電力を抑えることができる。

Event date： 2011.09.26   Language：Japanese  

本研究では，複数の光源の位置を同時に検出する
手法を提案する。まず,複数の光源をそれぞれ異なる
周波数に変調させて同時にPSD で受光させる．PSD
の出力は合成波となり，変調波のみ通過させるフィ
ルタ回路によって信号を抽出し,それぞれの光源の
位置を検出する。これにより, 非同期で複数光源の
位置を同時に検出することが可能になるので，LED
とPSD 間の通信量を大幅に削減できる．

Event date： 2011.09.26   Language：Japanese  

Event date： 2010.09.26   Language：Japanese  

Event date： 2010.09.26   Language：Japanese  

Event date： 2010.09.26   Language：Japanese  

Event date： 2010.09.03   Language：Japanese  

Event date： 2010.09.03   Language：Japanese  

Event date： 2010.09.03   Language：Japanese  

Event date： 2010.09.03   Language：Japanese  

Event date： 2010.09.02   Language：Japanese  

Event date： 2010.09.02   Language：Japanese  

Event date： 2010.06.18   Language：Japanese  

Event date： 2010.06.09 - 2010.06.11   Language：Japanese  

Event date： 2010.03.10   Language：Japanese  

Event date： 2009.09.04   Language：Japanese  

Event date： 2009.09.04   Language：Japanese  

Event date： 2009.06.10 - 2009.06.12   Language：Japanese  

Event date： 2005.11.20 - 2005.11.23   Language：English  

Event date： 2003.11.05 - 2003.11.07   Language：Japanese  

Event date： 2002.09.27   Language：Japanese  

Event date： 1998.09.27   Language：Japanese  

Event date： 1997.10.10 - 1997.10.11   Language：English  

Audience： High school students

Type：Visiting lecture