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All Technical Committee Conferences (Searched in: All Years)
| 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 | 2018-12-14 15:50 |
Miyagi | Bayes Boundary Estimation Capability Assessment for Large Geometric Margin Minimum Classification Error Training Ikuhiro Nishiyama (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Osaki (Doshisha Univ.) PRMU2018-92 |
The recent, Large Geometric Margin Minimum Classification Error training has, based on the smoothness of its smooth clas... [more] | PRMU2018-92 pp.91-96 |
|
| PRMU, CNR | 2017-02-18 11:20 |
Hokkaido | Small-sized Kernel Classifier By Support Vector Retraining Based on Minimum Classification Error Criterion Ryoma Tani (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Osaki (Doshisha Univ.) PRMU2016-159 CNR2016-26 |
Different from the Multi-class Support Vector Machine (MSVM) that fixes Support Vectors (SVs) to training samples, the K... [more] | PRMU2016-159 CNR2016-26 pp.41-46 |
|
| PRMU | 2015-12-21 09:30 |
Nagano | Evaluation of Automatic Prototype-Model Size Optimization in Large Geometric Margin Minimum Classification Error Training Masahiro Ogino (Doshisha Univ.), Hideyuki Watanabe (NICT), Shigeru Katagiri, Miho Osaki (Doshisha Univ.), Xugang Lu, Hisashi Kawai (NICT) PRMU2015-100 |
To develop a method for nding an appropriate class model size, which leads to accurate classi cation over unseen patter... [more] | PRMU2015-100 pp.1-6 |
|
| PRMU | 2015-12-22 15:20 |
Nagano | A Survey of Modified Quadratic Discriminant Function and its Application Tomoki Terada, Wataru Ohyama, Tetsushi Wakabayashi, Fumitaka Kimura (Mie Univ) PRMU2015-113 |
Modified Quadratic Discriminant Function (MQDF) is a discriminant function which significantly contributed for performan... [more] | PRMU2015-113 pp.129-141 |
|
| 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, 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 |
|
| IBISML | 2013-11-12 15:45 |
Tokyo | Tokyo Institute of Technology, Kuramae-Kaikan | [Poster Presentation]
Exaluation of Revised IP-OLDF with S-SVM, LDF and logistic regression by K-fold cross-validation Shuichi Shinmura (Seikei Univ.) IBISML2013-44 |
In this paper, Revised IP-OLDF based on MNM criterion is proposed using a mixed integer programming. The new discriminan... [more] | IBISML2013-44 pp.61-68 |
| 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 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2011-09-05 11:30 |
Hokkaido | Learning of Kernel Classfier based on General Loss Minimization Masato Ishii, Atsushi Sato (NEC) PRMU2011-61 IBISML2011-20 |
This paper presents a new method for learning kernel classifiers. First, we formulate a novel learning scheme called ``G... [more] | PRMU2011-61 IBISML2011-20 pp.23-30 |
|
| 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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