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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 #
MI 2012-01-19
10:45		 Okinawa   Improvement of RG/BH PET image quality using motion vector field estimated from inhalation and exhalation CT images
Masayuki Kanai (Chiba Univ.), Yoshitaka Tamai, Atsushi Sakohira, Kazuyoshi Suga (St. Hill Hospital), Hideaki Haneishi (Chiba Univ.) MI2011-80		 Lung motion due to respiration causes image degradation in medical imaging, especially in nuclear medicine which require... [more] MI2011-80
pp.17-22
MI 2011-01-19
17:35		 Okinawa Naha-Bunka-Tembusu Estimation of lung motion from CT images in different respiratory phases and its application to improvement of PET image quality
Masayuki Kanai (Chiba Univ.), Hideaki Haneishi (Chiba Univ. CFME), Kyouka Kobuna (Chiba Univ.), Hidenori Ue (FNCT), Yoshitaka Tamai, Atsushi Sakohira, Kazuyoshi Suga (St. Hill Hospital) MI2010-86		 Lung motion due to respiration causes image degradation in medical imaging, especially in nuclear medicine which require... [more] MI2010-86
pp.29-34
SP 2009-01-29
13:55		 Nara NAIST Error Detection in Speech Recognition using CRF Based on Various Linguistic Features
Tomohiko Matsumoto, Atsushi Sako, Tetsuya Takiguchi, Yasuo Ariki (Kobe Univ.) SP2008-127		 Recently, a learning method of n-gram showing error tendency is focused on. In this method, it is difficult to learn low... [more] SP2008-127
pp.7-12
SP, NLC 2008-12-09
15:35		 Tokyo Waseda Univ. Speech Recognition by Topic Models with Continuous/Discontinuous Topic Changes
Atsushi Sako, Yasuo Ariki (Kobe Univ.), Tomoharu Iwata, Shinji Watanabe, Takaaki Hori (NTT) NLC2008-33 SP2008-88		 In this paper, we propose topic models with continuous/discontinuous topic changes,
and describe experiments using MIT... [more]		 NLC2008-33 SP2008-88
pp.55-60
SP, NLC 2008-12-10
16:10		 Tokyo Waseda Univ. Language Model Adaptation by Topic Model Based on Sequence of Words
Atsushi Sako, Tetsuya Takiguchi, Yasuo Ariki (Kobe Univ.) NLC2008-66 SP2008-121		 It is important to consider semantics for reductions of recognition errors unlike humans
or understanding meanings and ... [more]		 NLC2008-66 SP2008-121
pp.249-254
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