A Supporting Technique for Comparative Analysis of Factory Work by Skilled and Unskilled Workers using Neural Network with Attention Mechanism

• Item type: Symposium(1)
• 公開日: 2021-06-23
• タイトル: A Supporting Technique for Comparative Analysis of Factory Work by Skilled and Unskilled Workers using Neural Network with Attention Mechanism
• タイトル / 言語: en
• タイトル: A Supporting Technique for Comparative Analysis of Factory Work by Skilled and Unskilled Workers using Neural Network with Attention Mechanism
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: 行動認識
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_5794
• 資源タイプ: conference paper
• 著者所属: Graduate School of Information Science and Technology, Osaka University
• 著者所属: Corporate Manufacturing Engineering Center, Toshiba Corporation
• 著者所属: Corporate Manufacturing Engineering Center, Toshiba Corporation
• 著者所属: Corporate Manufacturing Engineering Center, Toshiba Corporation
• 著者所属: Graduate School of Information Science and Technology, Osaka University
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Technology, Osaka University
• 著者所属(英): en
• 著者所属(英): Corporate Manufacturing Engineering Center, Toshiba Corporation
• 著者所属(英): en
• 著者所属(英): Corporate Manufacturing Engineering Center, Toshiba Corporation
• 著者所属(英): en
• 著者所属(英): Corporate Manufacturing Engineering Center, Toshiba Corporation
• 著者所属(英): en
• 著者所属(英): Graduate School of Information Science and Technology, Osaka University
• 著者名: Qingxin, Xia; Atsushi, Wada; Takanori, Yoshii; Yasuo, Namioka; Takuya, Maekawa
• 著者名(英): Qingxin, Xia; Atsushi, Wada; Takanori, Yoshii; Yasuo, Namioka; Takuya, Maekawa
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This study presents a method for identifying significant activity differences between skilled and unskilled factory workers by a neural network with an attention mechanism using wrist-worn accelerometer sensor data collected in real manufacturing. To discover skill knowledge from skilled workers, industrial engineers manually identify activity differences between skilled and unskilled workers, which is likely to obtain skill knowledge, by watching video recordings or sensor data. However, a factory has many workers and manual comparison between pairs of workers is time-consuming. We propose an attention-based neural network to visualize the importance of input segments that contribute to the classification output, which is useful to identify activity differences between workers.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This study presents a method for identifying significant activity differences between skilled and unskilled factory workers by a neural network with an attention mechanism using wrist-worn accelerometer sensor data collected in real manufacturing. To discover skill knowledge from skilled workers, industrial engineers manually identify activity differences between skilled and unskilled workers, which is likely to obtain skill knowledge, by watching video recordings or sensor data. However, a factory has many workers and manual comparison between pairs of workers is time-consuming. We propose an attention-based neural network to visualize the importance of input segments that contribute to the classification output, which is useful to identify activity differences between workers.
• 書誌情報: マルチメディア，分散協調とモバイルシンポジウム2021論文集; 巻 2021, 号 1, p. 1133-1140, 発行日 2021-06-23
• 出版者 / 言語: ja
• 出版者: 情報処理学会