陸 慧敏 (リク ケイビン)

LU Huimin

写真a

職名

准教授

研究室住所

福岡県北九州市戸畑区仙水町1-1

研究分野・キーワード

人工知能、ロボティックス、海中光学、コンピュータビジョン

ホームページ

https://ericlab.org/

取得学位 【 表示 / 非表示

  • 九州工業大学 -  博士(工学)  2014年03月

学内職務経歴 【 表示 / 非表示

  • 2019年09月
    -
    継続中

    九州工業大学   大学院工学研究院   機械知能工学研究系   准教授  

所属学会・委員会 【 表示 / 非表示

  • 2020年04月
    -
    継続中
     

    電子情報通信学会  日本国

  • 2019年12月
    -
    継続中
     

    情報処理学会  日本国

  • 2019年08月
    -
    継続中
     

    SPIE  アメリカ合衆国

  • 2012年01月
    -
    継続中
     

    IEEE  アメリカ合衆国

専門分野(科研費分類) 【 表示 / 非表示

  • 地球・資源システム工学

  • 知覚情報処理

  • 計測工学

 

論文 【 表示 / 非表示

  • Deep hierarchical encoding model for sentence semantic matching

    Lu W., Zhang X., Lu H., Li F.

    Journal of Visual Communication and Image Representation    71   2020年08月  [査読有り]

     概要を見る

    © 2020 Elsevier Inc. Sentence semantic matching (SSM) always plays a critical role in natural language processing. Measuring the intrinsic semantic similarity among sentences is very challenging and has not been substantially addressed. The latest SSM research usually relies on a shallow text representation and interaction between sentence pairs, which might not be enough to capture the complex semantic features and lead to limited performance. To capture more semantic context features and interactions, we propose a hierarchical encoding model (HEM) for sentence representation, further enhanced by a hierarchical matching mechanism for sentence interaction. Given two sentences, HEM generates intermediate and final representations in encoding layer, which are further handled by a novel hierarchical matching mechanism to capture more multi-view interactions in matching layer. The comprehensive experiments demonstrate that our model is capable to capture more sentence semantic features and interactions, which significantly outperforms the existing state-of-the-art neural models on the public real-world dataset.

    DOI Scopus

  • Effect of VR technology matureness on VR sickness

    Geršak G., Lu H., Guna J.

    Multimedia Tools and Applications    79 ( 21-22 ) 14491 - 14507   2020年06月  [査読有り]

     概要を見る

    © 2018, Springer Science+Business Media, LLC, part of Springer Nature. In this paper relationship of perceived virtual reality (VR) sickness phenomenon with different generations of virtual reality head mounted displays (VR HMD) is presented. Action content type omnidirectional video clip was watched by means of four HMDs of different levels of technological matureness, with a 2D monitor used as a reference point. In addition to subjective estimation of VR sickness effects by means of the SSQ questionnaire, psychophysiology of the participants was monitored. Participant’s electrodermal activity, heart rate, skin temperature and respiration rate were measured. Results of the study indicate differences between HMDs in both SSQ score and changes of physiology. Skin conductance was found to be significantly correlated with VR sickness. Mobile HMD did not induce significantly higher levels of VR sickness. Disorientation SSQ was proven to be a useful tool for assessing the VR sickness effects.

    DOI Scopus

  • Deep-Sea Organisms Tracking Using Dehazing and Deep Learning

    Lu H., Uemura T., Wang D., Zhu J., Huang Z., Kim H.

    Mobile Networks and Applications    25 ( 3 ) 1008 - 1015   2020年06月  [査読有り]

     概要を見る

    © 2018, Springer Science+Business Media, LLC, part of Springer Nature. Deep-sea organism automatic tracking has rarely been studied because of a lack of training data. However, it is extremely important for underwater robots to recognize and to predict the behavior of organisms. In this paper, we first develop a method for underwater real-time recognition and tracking of multi-objects, which we call “You Only Look Once: YOLO”. This method provides us with a very fast and accurate tracker. At first, we remove the haze, which is caused by the turbidity of the water from a captured image. After that, we apply YOLO to allow recognition and tracking of marine organisms, which include shrimp, squid, crab and shark. The experiments demonstrate that our developed system shows satisfactory performance.

    DOI Scopus

  • Detection of Circulating Tumor Cells in Fluorescence Microscopy Images Based on ANN Classifier

    Tsuji K., Lu H., Tan J.K., Kim H., Yoneda K., Tanaka F.

    Mobile Networks and Applications    25 ( 3 ) 1042 - 1051   2020年06月  [査読有り]

     概要を見る

    © 2018, Springer Science+Business Media, LLC, part of Springer Nature. Circulating tumor cells (CTCs) is a clinical biomarker for cancer metastasis. CTCs are cells circulating in the body of patients by being separated from primary cancer and entering into blood vessel. CTCs spread every positions in the body, and this is one of the cause of cancer metastasis. To analyze them, pathologists get information about metastasis without invasive test. CTCs test is conducted by analyzing the blood sample from patient. The fluorescence microscope generates a large number of images per each sample, and images contain a lot of cells. There are only a few CTCs in images and cells often have blurry boundaries. So CTCs identification is not an easy work for pathologists. In this paper, we develop an automatic CTCs identification method in fluorescence microscopy images. This proposed method has three section. In the first approach, we conduct the cell segmentation in images by using filtering methods. Next, we compute feature values from each CTC candidate region. Finally, we identify CTCs using artificial neural network algorithm. We apply the proposed method to 5895 microscopy images (7 samplesas), and evaluate the effectiveness of our proposed method by using leave-one-out cross validation. We achieve the result of performance tests, a true positive rate is 92.57% and false positive rate is 9.156%.

    DOI Scopus

  • Endmember Extraction of Hyperspectral Remote Sensing Images Based on an Improved Discrete Artificial Bee Colony Algorithm and Genetic Algorithm

    Fu Z., Pun C.M., Gao H., Lu H.

    Mobile Networks and Applications    25 ( 3 ) 1033 - 1041   2020年06月  [査読有り]

     概要を見る

    © 2018, Springer Science+Business Media, LLC, part of Springer Nature. Aiming at improving the performance of the endmember extraction problem in hyperspectral images, a new extraction method based on discrete hybrid artificial bee colony algorithm and genetic algorithm (DABC_GA) is proposed. By analyzing the characteristic of the problem, each dimension of candidate solution is a discrete and exclusive integer. Then we employ an optimization method with integral coding. By inheriting the strong exploration ability of the traditional artificial bee colony algorithm (ABC), we propose a discrete ABC which could quickly obtain more valuable endmembers combinations in the early stage. Then we select some outstanding results of DABC as the potential solutions of GA, which is adopted as another optimization tool in the later stage of iteration. The concept of complementary sets is proposed in the cross and mutation operators to guarantee the diversity and completeness of solutions. Meanwhile, the greedy strategy is adopted to ensure that the favorable potential solutions are not discarded. Compared with conventional extraction algorithms in simulated and real hyperspectral remote sensing data, the experimental results show the validity of our proposed algorithm.

    DOI Scopus

全件表示 >>

著書 【 表示 / 非表示

  • Cognitive Internet of Things: Frameworks, Tools and Applications

    Huimin LU ( 単著 )

    Springer International Publishing  2020年01月 ISBN: 978-3-030-04945-4

  • Artificial Inteligence and Robotics

    Huimin Lu, Xing Xu ( 共編者 )

    Springer  2017年12月 ISBN: 978-3-319-69877-9

  • Artificial Intelligence and Computer Vision

    Huimin Lu, Yujie Li ( 共編者 )

    Springer  2016年11月

講演 【 表示 / 非表示

  • AIを活用した水中画像処理技術と深海資源調査への展開

    第1回海中海底工学フォーラム・ZERO   2019年04月12日 

  • Artificial Intelligence in Deep-sea Observing

    The 2nd International Symposium on Artificial Intelligence and Robotics 2017 ( Kitakyushu, Japan )  2017年11月25日  ISAIR

  • Extreme Optical Imaging for Deep-sea Observing Network

    26th International Electrotechnical and Computer Science Conference ERK 2017 ( Congress Center Bernardin, Portorož, Slovenia )  2017年09月25日  IEEE Slovenia

  • Next Generation Artificial Intelligence in Society 5.0

    IBM Australia Seminar ( Melbourne, Australia )  2017年09月04日  IBM Australia

科研費獲得実績 【 表示 / 非表示

  • 日中超スマート社会の実現に向けた次世代のAI/IoTに関する研究

    二国間国際交流事業

    研究期間:  2018年04月  -  2019年03月

    研究課題番号:  00000001

  • 深海採鉱機採削時の画像計測システムの研究開発

    若手研究(B)

    研究期間:  2017年04月  -  2019年03月

    研究課題番号:  17K14694

  • 深海採鉱機向けリアルタイム小型イメージングシステムの研究開発

    特別研究員奨励費

    研究期間:  2015年04月  -  2016年09月

    研究課題番号:  15F15077

  • 深海採鉱機向け鉱床計測用リアルタイム画像採取処理装置の研究開発

    特別研究員奨励費

    研究期間:  2013年04月  -  2015年03月

    研究課題番号:  13J10713

受託研究・共同研究実施実績 【 表示 / 非表示

  • 国立研究開発法人情報通信研究機構国際交流プログラム

    受託研究

    研究期間:  2018年04月  -  2019年03月

  • 国立情報学研究所共同研究

    受託研究

    研究期間:  2018年04月  -  2019年03月

寄附金・講座 【 表示 / 非表示

  • 公益財団法人電気通信普及財団 研究調査助成

    公益財団法人電気通信普及財団  2019年05月

  • 電気通信普及財団研究調査助成

    公益財団法人電気通信普及財団  2018年05月

  • 造船学術研究推進機構 助成金

    造船学術研究推進機構  2017年08月

  • 電気通信普及財団 研究調査助成

    公益財団法人電気通信普及財団  2017年04月

 

学会・委員会等活動 【 表示 / 非表示

  • 2019年08月
    -
    継続中

    IEEE Computer Society Big Data Special Technical Committee   共同委員長

 

国際会議の開催 【 表示 / 非表示

  • EAI International Conference on Robotic Sensor Networks

    2017年11月25日  -  2017年11月26日 

  • The 2nd International Symposium on Artificial Intelligence and Robotics 2017

    2017年11月25日  -  2017年11月26日 

  • The 1st International Symposium on Artificial Intelligence and Robotics 2016

    China  2016年12月13日  -  2016年12月13日  Huimin Lu

国際交流窓口担当 【 表示 / 非表示

  • リュブリャナ大学  2018年11月  -  継続中

  • 南京郵電大学 オートメーション工学部  2018年05月  -  継続中