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Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU 2011-03-10
11:10		 Ibaraki   Simultaneous Optimization of Context Clustering and GMM for Offline Handwritten Word Recognition Using HMM
Tomoyuki Hamamura (Toshiba/Univ. of Tokyo), Bunpei Irie (Toshiba), Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (Univ. of Tokyo) PRMU2010-244		 Context-dependent HMM is commonly used in speech recognition. The model can be realized by two ways: context clustering ... [more] PRMU2010-244
pp.43-48
PRMU 2008-02-22
15:30		 Ibaraki Univ. of Tsukuba Strategy of Multistage Pattern Recognition Using a Posteriori Probability and Best-first Search -- Application to Address Recognition --
Tomoyuki Hamamura, Takuma Akagi, Bunpei Irie (TOSHIBA) PRMU2007-243		 For faster recognition, coarser classifiers are often employed for pre-classification forming a multi-stage classificati... [more] PRMU2007-243
pp.167-172
PRMU 2007-03-15
11:30		 Okayama   An Analytic Word Recognition Algorithm Using a Posteriori Probability -- Normalization of the number of segmentation candidates --
Tomoyuki Hamamura, Takuma Akagi, Bunpei Irie (TOSHIBA Corp.) 		Word recognition algorithms are classified into two major groups. One is an "analytic" approach of recognizing individua... [more] PRMU2006-238
pp.19-24
PRMU, NLC, TL 2006-10-19
09:00		 Tokyo   An Evaluation Function Based on a Posteriori Probability for Word Recognition
Tomoyuki Hamamura, Takuma Akagi, Bunpei Irie (Toshiba Corp.) 		Handwritten word recognition algorithms are classified into two major groups. One is "analytic" approach of recognizing ... [more] PRMU2006-92
pp.1-6
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