Art

J-GLOBAL ID：201902214941149096   Reference number：19A2174733

On Input/Output Architectures for Convolutional Neural Network-Based Cross-View Gait Recognition

畳込みニューラルネットワークに基づくクロスビュー歩容認識のための入出力アーキテクチャについて【JST・京大機械翻訳】

Author (5)： Takemura Noriko (Mitsubishi Electric Collaborative Research Division for Wide-Area Security Technology, Institute of the Scientific and Industrial Research, Osaka University, Osaka, Japan) ,  Makihara Yasushi (Mitsubishi Electric Collaborative Research Division for Wide-Area Security Technology, Institute of the Scientific and Industrial Research, Osaka University, Osaka, Japan) ,  Muramatsu Daigo (Mitsubishi Electric Collaborative Research Division for Wide-Area Security Technology, Institute of the Scientific and Industrial Research, Osaka University, Osaka, Japan) ,  Echigo Tomio (Department of Engineering Informatics, Osaka Electro-Communication University, Osaka, Japan) ,  Yagi Yasushi (Mitsubishi Electric Collaborative Research Division for Wide-Area Security Technology, Institute of the Scientific and Industrial Research, Osaka University, Osaka, Japan)
Material： IEEE Transactions on Circuits and Systems for Video Technology  (IEEE Trans Circuits Syst Video Technol)
Volume： 29  Issue： 9  Page： 2708-2719  Publication year： 2019 
JST Material Number： W0321A  ISSN： 1051-8215  CODEN： ITCTEM  Document type： Article
Article type： 原著論文  Country of issue： United States (USA)  Language： ENGLISH (EN)

Abstract/Point： In this paper, we discuss inpu...

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Thesaurus term： *convolution ,  *network ,  benchmark ,  *computer architecture ,  grading (ranking) ,  triplet ,  *gait identification ,  *convolutional neuralnetwork

JST classification (1)： Graphic and image processing in general  (JE04010I)

Terms in the title (4)： 畳込みニューラルネットワーク ,  歩容認識 ,  入出力 ,  アーキテクチャ