| ○種別 (必須): | □ | 学術論文 (審査論文)
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| ○言語 (必須): | □ | 英語
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| ○招待 (推奨): |
| ○審査 (推奨): | □ | Peer Review
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| ○カテゴリ (推奨): | □ | 研究
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| ○学究種別 (推奨): |
| ○組織 (推奨): |
| ○著者 (必須): | 1. | (英) Sun, Xiao (日) (読)
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| 2. | (英) Pan, Ting (日) (読)
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| 3. | 任 福継 (->個人[中川 福継])
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| ○貢献度 (任意): |
| ○学籍番号 (推奨): |
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| ○題名 (必須): | □ | (英) Facial Expression Recognition Using ROI-KNN Deep Convolutional Neural Networks (日)
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| ○要約 (任意): | □ | (英) Deep neural networks have been proved to be able to mine distributed representation of data including image, speech and text. By building two models of deep convolutional neural networks and deep sparse recti¯er neural networks on facial expression dataset, we make contrastive evaluations in facial expression recognition system with deep neural networks. Additionally, combining region of interest (ROI) and K-nearest neighbors (KNN), we propose a fast and simple improved method called OI-KNN" for facial expression classi¯cation, which relieves the poor generalization of deep neural networks due to lacking of data and decreases the testing error rate apparently and generally. The proposed method also improves the robustness of deep learning in facial expression classi¯cation. (日)
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| ○キーワード (推奨): | 1. | (英) Convolution neural networks (日) 俗語 (読)
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| 2. | (英) facial expression recognition (日) トピック分析 (読)
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| 3. | (英) model generalization (日) 時系列分析 (読)
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| 4. | (英) prior knowledge (日) (読)
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| ○発行所 (推奨): |
| ○誌名 (必須): | □ | (英) ACTA AUTOMATICA SINICA (日) (読)
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| ○巻 (必須): | □ | 42
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| ○号 (必須): | □ | 6
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| ○頁 (必須): | □ | 883 891
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| ○都市 (任意): |
| ○年月日 (必須): | □ | 西暦 2016年 6月 初日 (平成 28年 6月 初日)
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| ○URL (任意): | □ | http://www.aas.net.cn/CN/abstract/abstract18879.shtml
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| ○DOI (任意): | □ | 10.16383/j.aas.2016.c150638 (→Scopusで検索)
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