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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, 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 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 |
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| 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 |
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| PRMU, CNR | 2018-02-20 11:45 |
Wakayama | A Classification-Uncertainty-Based Criterion for Classification Boundary Selection David Ha (Doshisha Univ.), Juliette Maes (ECL), Yuya Tomotoshi (Doshisha Univ.), Hideyuki Watanabe (ATR), Shigeru Katagiri, Miho Osaki (Doshisha Univ.) PRMU2017-166 CNR2017-44 |
[more] | PRMU2017-166 CNR2017-44 pp.121-126 |
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| 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 |
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| 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 |
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| SP, IPSJ-SLP (Joint) |
2015-07-16 17:20 |
Nagano | Katakura Suwako Hotel | Experimental evaluation of network size effect in speaker adaptive trained DNNs embedding linear transformation networks Tsubasa Ochiai (Doshisha Univ./NICT), Shigeki Matsuda (Doshisha Univ.), Hideyuki Watanabe, Xugang Lu, Hisashi Kawai (NICT), Shigeru Katagiri (Doshisha Univ.) SP2015-41 |
Recently we proposed a novel speaker adaptation method that applied the Speaker Adaptive Training (SAT) concept to DNN-... [more] |
SP2015-41 pp.31-36 |
| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| 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 |
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| LQE, LSJ | 2013-05-17 15:20 |
Ishikawa | Optical and spin properties of nitrogen-vacancy centers in diamond fabricated using nitrogen-doped isotopically-enriched chemical vapor deposition Tomohiro Gomi, Shuhei Tomizawa (Keio Univ.), Hideyuki Watanabe, Hitoshi Umezawa, Shin-ichi Shikata (AIST), Kohei M. Itoh, Junko Ishi-Hayase (Keio Univ.) LQE2013-12 |
An electronic spin state of nitrogen-vacancy (NV) centers in diamond is expected as an promising candidate for quantum i... [more] | LQE2013-12 pp.53-56 |
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| 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 |
|
| EMD | 2011-03-04 14:30 |
Saitama | Nippon Institute of Technology | Comparison of hauling force between series & parallel connection of electric motor by readhesion control in 5-inches large model electric locomotive Hideyuki Watanabe, Hidenori Ito, Daichi Kawarahata, Naohiro Saito, Yu Yifan, Kiyoshi Onodera, Lu Zijun, Makoto Takanezawa, Noboru Morita (Nippon Inst. of Tech.) EMD2010-160 |
This research is in association with improvement of hauling force for electric rolling stock. In recent years, as a res... [more] |
EMD2010-160 pp.33-36 |
| 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 |
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