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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
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Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU 2022-09-14
10:00		 Kanagawa
(Primary: On-site, Secondary: Online)		 Sampling-based path planning using trajectories obtained by reinforcement learning
Keigo Kamiyama, Kei Ota, Ryosuke Takanami, Asako Kanezaki (Tokyo Tech) PRMU2022-10		 We propose a path planning method that considers dynamics constraints by using the past trajectories obtained through re... [more] PRMU2022-10
pp.1-6
PRMU, IPSJ-CVIM, MVE [detail] 2017-01-20
13:00		 Kyoto   A Report on MIRU2016 Young Researchers' Program
Takuya Funatomi (NAIST), Masato Ishii (NEC), Nakamasa Inoue (Tokyo Tech), Asako Kanezaki (AIST), Kosuke Takahashi (NTT), Keisuke Doman (Chukyo Univ.), Takahiro Yoshioka (Fujitsu Labs.) PRMU2016-143 MVE2016-34		  [more] PRMU2016-143 MVE2016-34
pp.283-290
PRMU 2014-10-09
15:00		 Chiba   Learning Similarities for Rigid and Non-Rigid Object Detection
Asako Kanezaki (Univ. of Tokyo), Emanuele Rodola, Daniel Cremers (Technische Univ. Munchen), Tatsuya Harada (Univ. of Tokyo) PRMU2014-56		 We propose an optimization method for estimating parameters in graph-theoretical formulations of the matching problem fo... [more] PRMU2014-56
pp.13-18
PRMU, IBISML, IPSJ-CVIM
(Joint) [detail]		 2012-09-03
09:30		 Tokyo   Simultaneous training of multi-class object detectors via large scale image dataset -- introduction of target specific negative classes --
Asako Kanezaki, Sho Inaba, Yoshitaka Ushiku, Yuya Yamashita, Hiroshi Muraoka, Tatsuya Harada, Yasuo Kuniyoshi (Univ. Tokyo) PRMU2012-42 IBISML2012-25		 We propose an efficient method to train multiple object detectors simultaneously using a large-scale image dataset. The ... [more] PRMU2012-42 IBISML2012-25
pp.105-112
PRMU 2009-11-27
13:30		 Ishikawa Ishikawa Industrial Promotion Center Application of High-speed 3D Object Recognition in the Real World Using Integral Features and Linear Subspace Method
Asako Kanezaki, Tatsuya Harada, Yasuo Kuniyoshi (Univ. of Tokyo.) PRMU2009-123		 As a previous work, we proposed a method of high-speed 3D object recognition using linear subspace method and our 3D fea... [more] PRMU2009-123
pp.207-212
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