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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 20 of 26  /  [Next]  
Committee Date Time Place Paper Title / Authors Abstract Paper #
PRMU, IPSJ-CVIM 2020-03-17
16:50
Kyoto
(Cancelled but technical report was issued)
Experimental Evaluation for Bayes Error Estimation Capability of Large Geometric Margin Minimum Classification Error Training
Ikuhiro Nishiyama (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2019-99
Previous studies suggested that the Large Geometric Margin-Minimum Classification Error (LGM-MCE) training method had th... [more] PRMU2019-99
pp.231-236
PRMU, IPSJ-CVIM 2020-03-17
17:05
Kyoto
(Cancelled but technical report was issued)
Experimental Evaluation on Bayes Error Estimation Capability of Kernel Minimum Classification Error Training
Koji Yamada (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2019-100
A pattern classifier incorporating kernel mapping, which is trained by the Kernel Minimum Classification Error (KMCE) tr... [more] PRMU2019-100
pp.237-242
PRMU, IPSJ-CVIM 2020-03-17
17:20
Kyoto
(Cancelled but technical report was issued)
Study on Maximum Bayes Boundary-ness Training for Pattern Classification
Masahiro Senda, David Ha (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2019-101
 [more] PRMU2019-101
pp.243-248
PRMU 2018-12-14
16:05
Miyagi   Experimental Evaluation of Automatic Determination of Loss Smoothness for Minimum Classification Error Training
Kazuma Kobayashi (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2018-93
(To be available after the conference date) [more] PRMU2018-93
pp.97-102
PRMU, IPSJ-CVIM, MVE [detail] 2015-01-23
09:50
Nara   Analysis of Minimum Classification Error Training using Bit-String-Based Genetic Algorithms
Hiroto Togoe (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri (Doshisha Univ.), Xugang Lu, Chiori Hori (NICT), Miho Ohsaki (Doshisha Univ.) PRMU2014-100 MVE2014-62
Minimum Classification Error (MCE) training using gradient-descent-based loss minimization does not guarantee a global m... [more] PRMU2014-100 MVE2014-62
pp.171-176
PRMU, IPSJ-CVIM, MVE [detail] 2015-01-23
10:15
Nara   Relation between Data Grouping and Robustness to Unseen Data in Large Geometric Margin Minimum Classification Error Training
Hiroyuki Shiraishi (Doshisha Univ), Hideyuki Watanabe (NICT), Shigeru Katagiri (Doshisha Univ), Xugang Lu, Chiori Hori (NICT), Miho Ohsaki (Doshisha Univ) PRMU2014-101 MVE2014-63
To develop a pattern classifier that is robust to unseen pattern samples, classifier parameters have been conventionally... [more] PRMU2014-101 MVE2014-63
pp.177-182
PRMU 2014-03-14
15:30
Tokyo   Experimental study on effect of pre-training in deep learning through visualization of unit outputs
Tsubasa Ochiai (Doshisha Univ./NICT), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-210
To clarify the capability of recent powerful classifier concept, Deep Neural Networks (DNN), we experimentally
investig... [more]
PRMU2013-210
pp.253-258
PRMU, IPSJ-CVIM, MVE [detail] 2014-01-23
09:30
Osaka   Minimum Classification Error Training with Automatic Determination of Loss Smoothness Common to All Classes
Kensuke Ota (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-91 MVE2013-32
The smoothness of the smooth classification error count loss used in the Minimum Classification Error (MCE) training has... [more] PRMU2013-91 MVE2013-32
pp.1-6
PRMU, IPSJ-CVIM, MVE [detail] 2014-01-23
10:00
Osaka   Minimum Classification Error Training with Automatic Control of Loss Smoothness
Hideaki Tanaka (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-92 MVE2013-33
The Minimum Classification Error (MCE) training has been successfully applied to various types of classifiers. However, ... [more] PRMU2013-92 MVE2013-33
pp.7-12
PRMU, IPSJ-CVIM, MVE [detail] 2014-01-23
10:30
Osaka   Multi-Class Support Vector Machine based on Minimum Classification Error Criterion
Hisashi Uehara (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-93 MVE2013-34
Gradient-descent-based optimization methods used in Minimum Classification Error (MCE) training are not necessarily easi... [more] PRMU2013-93 MVE2013-34
pp.13-18
PRMU, IPSJ-CVIM, MVE [detail] 2014-01-23
11:00
Osaka   Large Geometric Margin Minimum Classification Error Training with Automatic Optimization Of The Number of Prototypes
Yuji Takayama (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.), Shigeki Matsuda, Chiori Hori (NICT) PRMU2013-94 MVE2013-35
Large Geometric Margin Minimum Classification Error (LGM-MCE) training, which adopts geometric-margin-based misclassific... [more] PRMU2013-94 MVE2013-35
pp.19-24
EA 2013-10-11
13:00
Kyoto NTT CS Lab. Experimental Evaluation of Sound Image Localization Accuracy Affected by Visual Image for Acoustic Barrier Method
Hiroaki Sawasaki, Haruka Yamashita, Akihiro Nakatani, Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) EA2013-65
 [more] EA2013-65
pp.9-16
ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] 2012-02-20
15:40
Hokkaido Hokkaido Univ. Experimental Evaluation of Image Object Tracking Method using Particle Filter and Minimum Classification Error Training
Jyun'ichi Nakamura, Shigeru Katagiri, Miho Ohsaki (Doshisha Univ) ITS2011-36 IE2011-112
To increase the accuracy of image object tracking, a discriminative tracking method was proposed that combined the parti... [more] ITS2011-36 IE2011-112
pp.79-84
ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] 2012-02-21
15:00
Hokkaido Hokkaido Univ. User Tracking with Multiple Camera Images for a Remote Collaboration Support System called "t-Room"
Kana Takeuchi, Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) ITS2011-55 IE2011-131
To increase the utility of a remote collaboration support system called "t-Room", we investigated in this paper a user t... [more] ITS2011-55 IE2011-131
pp.319-324
ITS, IE, ITE-AIT, ITE-HI, ITE-ME [detail] 2012-02-21
15:20
Hokkaido Hokkaido Univ. Improvement of an Image Object Extraction Method for Remote Collaboration Support System "t-Room"
Yuzuru Nakamura, Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) ITS2011-56 IE2011-132
To alleviate the problem of “visual echo” for a recent remote collaboration support system called “t-Room”, an backgroun... [more] ITS2011-56 IE2011-132
pp.325-330
PRMU 2011-03-11
09:30
Ibaraki   Application of Automatic Loss Smoothness Control to Large Geometric Margin Minimum Classification Error Training
Tsukasa Ohashi (Doshisha Univ.), Hideyuki Watanabe (NICT), Jun'ichi Tokuno, Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2010-270
A method that automatically controls the smoothness of a smoothed classification error count loss using Parzen estimatio... [more] PRMU2010-270
pp.195-200
PRMU, FM 2010-12-09
16:40
Yamaguchi   Large Geometric Margin Minimum Classification Error Training for Kernel-based High Dimensional Space
Hideyuki Watanabe (NICT), Shigeru Katagiri, Mamoru Adachi, Miho Ohsaki (Doshisha Univ.) PRMU2010-136
Large Geometric Margin Minimum Classification Error (LGM-MCE) training has been successfully applied to multi-class clas... [more] PRMU2010-136
pp.55-60
PRMU, FM 2010-12-10
15:20
Yamaguchi   Comparison between Minimum Classification Error Training and Support Vector Machine in Prototype-based Classifier Design
Mamoru Adachi (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2010-146
In this paper, we experimentally compared the size of trained classifier class models (prototypes) between Support Vecto... [more] PRMU2010-146
pp.107-112
IBISML, PRMU, IPSJ-CVIM [detail] 2010-09-06
10:40
Fukuoka Fukuoka Univ. Minimum Classification Error Training with Automatic Control of Loss Smoothness
Junichi Tokuno (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Ohsaki (Doshisha Univ.) PRMU2010-80 IBISML2010-52
The smoothness embedded in the Minimum Classification Error formalization has an effect of increasing virtual training s... [more] PRMU2010-80 IBISML2010-52
pp.179-184
PRMU 2009-11-27
13:00
Ishikawa Ishikawa Industrial Promotion Center Finger Recognition using Particle Filter and Minimum Classification Error Training
Kosuke Kiyota, Shigeru Katagiri (Doshisha Univ.), Hideyuki Watanabe (NICT), Miho Ohsaki (Doshisha Univ.) PRMU2009-125
This paper proposes a new method for recognizing a finger used as a pointer to operate a remote collaboration assistant ... [more] PRMU2009-125
pp.235-240
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