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Committee Date Time Place Paper Title / Authors Abstract Paper #
MI, MICT 2017-11-06
10:00		 Kagawa Sunport Hall Takamatsu Automated Initialization of 2D-3D Registration of Rib Cage from Chest Radiography using Convolutional Neural Network
Mototaka Kabashima, Yuta Hiasa, Yoshito Otake (NAIST), Rie Tanaka, Shigeru Sanada (Kanazawa Univ.), Yoshinobu Sato (NAIST) MICT2017-27 MI2017-49		 The difficulties in automation of 2D-3D registration are two-folds: initialization and failure detection. In this paper,... [more] MICT2017-27 MI2017-49
pp.5-8
VLD, DC, CPSY, RECONF, CPM, ICD, IE
(Joint) [detail]		 2016-11-29
10:30		 Osaka Ritsumeikan University, Osaka Ibaraki Campus Accurate Lithography Simulation Model based on Deep Learning
Yuki Watanabe, Tetsuaki Matsunawa, Taiki Kimura, Shigeki Nojima (Toshiba) VLD2016-56 DC2016-50		 Lithography simulation is an indispensable technology for today's semiconductor manufacturing processes. To achieve accu... [more] VLD2016-56 DC2016-50
pp.73-78
PRMU, CNR 2015-02-20
14:50		 Miyagi   Predicting User Demographics and Click Through Rate of Display Ads Applying a Generic Image Recognition Methodology
Kohei Yamamoto (The Univ. of Tokyo), Tetsuya Motegi, Yukihiro Tagami, Hayato Kobayashi, Shingo Ono (Yahoo Japan), Hideki Nakayama (The Univ. of Tokyo) PRMU2014-149 CNR2014-64		 In the field of click-through rate (CTR) prediction of pay per click display ads, the latency and the cold-start problem... [more] PRMU2014-149 CNR2014-64
pp.179-184
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