ARAI Satoshi

Affiliation

Faculty of Environment and Information Sciences, Division of Social Environment and Information

Job Title

Specially Appointed Professor

Research Fields, Keywords

Image Processing,Image Recognition, Machine Learning, Neural Networks, Artificial Intelligence


The Best Research Achievement in Research Career 【 display / non-display

  • 【Published Thesis】 Non-strict Attentional Region Annotation to Improve Image Classification Accuracy  2021.10

    【Published Thesis】 Intuitive Visualization Method for Image Classification Using Convolutional Neural Networks  2017.07

    【Published Thesis】 Deep Zero-mean Normalized Cross Correlation Networks  2018.07

The Best Research Achievement in the last 5 years 【 display / non-display

  • 【Published Thesis】 Non-strict Attentional Region Annotation to Improve Image Classification Accuracy  2021.10

Degree 【 display / non-display

  • 博士(工学) - 横浜国立大学

  • 修士(工学) - 東京工業大学

Campus Career 【 display / non-display

  • 2020.12
     
     

    Duty   Yokohama National UniversityFaculty of Environment and Information Sciences   Division of Social Environment and Information   Specially Appointed Professor  

Academic Society Affiliations 【 display / non-display

  • 2010.6
     
     
     

    情報処理学会

Research Areas 【 display / non-display

  • Informatics / Intelligent informatics

 

Thesis for a degree 【 display / non-display

  • Toward Explainable Deep Network Models

    Satoshi Arai

    2019.3

    Doctoral Thesis   Single Work  

Papers 【 display / non-display

  • Intuitive Visualization Method for Image Classification Using Convolutional Neural Networks

    Satoshi Arai, Tomoharu Nagao

    10 ( 2 )   1 - 13   2017.7  [Reviewed]

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

  • Non-strict Attentional Region Annotation to Improve Image Classification Accuracy

    Arai Satoshi, Shirakawa Shinichi, Nagao Tomoharu

    2021 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)   2375 - 2380   2021.10  [Reviewed]

    DOI Web of Science

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

  • Evolutionary Generative Contribution Mappings

    Kobayashi Masayuki, Arai Satoshi, Nagao Tomoharu

    2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)   1657 - 1664   2020

    Web of Science

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

  • SSD Net: Toward Deep Network Models based on Dissimilarity Metrics

    荒井 敏,長尾 智晴

    Joint International Workshop on Advanced Image Technology and International Forum on Medical Imaging in Asia (IWAIT-IFMIA2019)   2019.1  [Reviewed]

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

  • Deep Zero-mean Normalized Cross Correlation Networks

    Satoshi Arai, Tomoharu Nagao

    11 ( 2 )   12 - 21   2018.7  [Reviewed]

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

Presentations 【 display / non-display

  • Non-strict Attentional Region Annotation to Improve Image Classification Accuracy

    Satoshi Arai, Shinichi Shirakawa, Tomoharu Nagao

    2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC) 

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    Event date: 2021.10

    Language:English   Presentation type:Oral presentation (general)  

    Venue:Melbourne, Australia  

  • SSD Net: Toward Deep Network Models based on Dissimilarity Metrics

    Satoshi Arai, Tomoharu Nagao

    Joint International Workshop on Advanced Image Technology and International Forum on Medical Imaging in Asia (IWAIT-IFMIA2019) 

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    Event date: 2019.1

    Language:English   Presentation type:Oral presentation (general)  

  • 深層零平均正規化相互相関ネットワーク

    荒井 敏, 長尾 智晴

    第116回 MPS研究会  情報処理学会

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    Event date: 2017.12

    Language:Japanese   Presentation type:Oral presentation (general)  

  • 畳み込みニューラルネットワークを用いた画像分類タスクの直感的可視化方法

    荒井 敏, 長尾 智晴

    第111回 MPS研究会  情報処理学会

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    Event date: 2016.12

    Language:Japanese   Presentation type:Oral presentation (general)