Art

J-GLOBAL ID：201802221261422688   Reference number：18A0376242

Daily Activity Recognition with Large-Scaled Real-Life Recording Datasets Based on Deep Neural Network Using Multi-Modal Signals

マルチモーダル信号を用いた深層ニューラルネットワークに基づく大規模実時間記録データセットによる日常活動認識

Author (5)： HAYASHI Tomoki (Graduate School of Information Science, Nagoya University) ,  NISHIDA Masafumi (Graduate School of Information, Shizuoka University) ,  KITAOKA Norihide (Graduate School of Science and Technology, Tokushima University) ,  TODA Tomoki (Information Technology Center, Nagoya University) ,  TAKEDA Kazuya (Graduate School of Information Science, Nagoya University)
Material： IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences (Web)  (IEICE Trans Fundam Electron Commun Comput Sci (Web))
Volume： E101.A  Issue： 1  Page： 199-210(J-STAGE)  Publication year： 2018 
JST Material Number： U0466A  ISSN： 1745-1337  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： communication system ,  communication signal ,  *neural network (biomodel) ,  *set ,  *real time processing ,  *activity of daily living ,  *recognition ,  Smartphone ,  monitor ,  photographic camera ,  Sound ,  acceleration (ratio) ,  database ,  miniature camera ,  environmental sound ,  *deep neural network
Semi thesaurus term： multimodal communication ,  *deep neural network ,  *large data sets ,  *activity recognition

Author keywords (5)： human activity recognition ,  activity of daily living ,  database ,  deep neural networks ,  adaptation

JST classification (3)： Pattern recognition  (JE07000S) ,  Artificial intelligence  (JE08000Z) ,  Database systems  (JD03030U)

Reference (40)：

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Terms in the title (6)： マルチモーダル ,  深層ニューラルネットワーク ,  大規模 ,  実時間 ,  記録データ ,  活動認識