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Technical Committee on Artificial Intelligence and Knowledge-Based Processing (AI)  (Searched in: 2019)

Search Results: Keywords 'from:2019-11-28 to:2019-11-28'
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Search Results: Conference Papers
 Conference Papers (Available on Advance Programs)  (Sort by: Date Ascending)
 Results 1 - 8 of 8  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
AI 2019-11-28
13:05		 Fukuoka   A proposal of a method for analyzing causes of incorrect detection when detecting objects using Deep Learning
Tomonori Kubota, Takanori Nakao, Eiji Yoshida (Fujitsu Lab.) AI2019-30		 In this paper, we propose a method for analyzing the causes of incorrect detection / poor accuracy when detecting object... [more] AI2019-30
pp.1-6
AI 2019-11-28
13:30		 Fukuoka   On a Method for Constructing a Mahjong Tile Detector from Abstract Training Data
Ryosuke Suzuki, Tadachika Ozono, Toramatsu Shintani (NIT) AI2019-31		 Constructing a detector needs constructing dataset which consists various scenes. We generate synthesize images based on... [more] AI2019-31
pp.7-12
AI 2019-11-28
13:55		 Fukuoka   Realizing a Video Editing System for Flipped Classrooms with AR Puppets
Hitomi Kataoka, Tadachika Ozono, Toramatsu Shintani (NIT) AI2019-32		 In this study, we develop a new video editing system for flipped classrooms with AR (Augmented Reality) technologies. We... [more] AI2019-32
pp.13-18
AI 2019-11-28
14:20		 Fukuoka   Action Planning considering State of Agents for Multi-Agent Pickup and Delivery
Tomoki Yamauchi, Yuki Miyashita, Toshiharu Sugawara (Waseda Univ.) AI2019-33		 (To be available after the conference date) [more] AI2019-33
pp.19-24
AI 2019-11-28
15:15		 Fukuoka   Effectiveness of feature selection as pre-processing of LSTM using W2V
Shiori Koga, Tsunenori Mine, Sachio Hirokawa (Kyushu Univ.) AI2019-34		 Among RNNs, especially LSTM is capable of long-term memory, and can be expected to acquire information including better ... [more] AI2019-34
pp.25-30
AI 2019-11-28
15:40		 Fukuoka   Emotion Learning from Emotion Tags and Comparative Experience with LSTM and GRU -- Heading toward Sublimation from Desktop Mascot to AI Agent --
Kuniaki Yuba, Eisuke Ito (Kyudai) AI2019-35		 Dialogue Programs have improved their performances by using GPU and Servers.But, their characters are low diversity and ... [more] AI2019-35
pp.31-36
AI 2019-11-28
16:05		 Fukuoka  
Keisuke Ikeda, Kazufumi Kojima, Masahiro Tani (NEC Corporation) AI2019-36		  [more] AI2019-36
pp.37-42
AI 2019-11-28
16:30		 Fukuoka   Prediction of Gene Mutation Position by Machine Learning and Feature Selection
Sachio Hirokawa (Kyushu Univ.), Tetsuji Kuboyama (Gakushin Univ.), Koichi Hirata (Kyutech) AI2019-37		  [more] AI2019-37
pp.43-45
 Results 1 - 8 of 8  /   
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