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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MI | 2022-01-27 13:54 |
Online | Online | [Short Paper]
Case-based Similar Image Retrieval for Pathological Images of Malignant Lymphoma Using Deep Metric Learning Noriaki Hashimoto (RIKEN), Yusuke Takagi, Hiroki Masuda (NITech), Hiroaki Miyoshi, Kei Kohno, Miharu Nagaishi, Kensaku Sato, Koichi Ohshima (Kurume Univ.), Hidekata Hontani (NITech), Ichiro Takeuchi (NITech/RIKEN)  MI2021-78 |
We propose a novel method of case-based similar image retrieval for histopathological images of malignant lymphoma. We e... [more] | MI2021-78 pp.144-145 |
| BioX, ISEC, SITE, ICSS, EMM, HWS, IPSJ-CSEC, IPSJ-SPT [detail] | 2021-07-19 16:55 |
Online | Online | Evaluation on Biometric Template Protection System Based on Somewhat Homomorphic Encryption Hiroto Tamiya, Toshiyuki Isshiki, Kengo Mori (NEC), Satoshi Obana (Hosei Univ.), Tetsushi Ohki (Shizuoka Univ.) ISEC2021-21 SITE2021-15 BioX2021-22 HWS2021-21 ICSS2021-26 EMM2021-26 |
Many biometric template protection systems have been proposed to perform biometric authentication while keeping the biom... [more] | ISEC2021-21 SITE2021-15 BioX2021-22 HWS2021-21 ICSS2021-26 EMM2021-26 pp.68-73 |
| ITS, IE, ITE-MMS, ITE-HI, ITE-ME, ITE-AIT [detail] | 2019-02-20 10:45 |
Hokkaido | Hokkaido Univ. | A note on retrieval of similar inspection records based on distance metric learning for supporting maintenance of subway tunnels Susumu Genma, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama (Hokkaido Uinv) |
This paper proposes a method to retrieve similar inspection records using distance metric learning for supporting tunnel... [more] | |
| IBISML | 2017-11-10 13:00 |
Tokyo | Univ. of Tokyo | Safe Screening for Large Margin Metric Learning Tomoki Yoshida (NITech), Ichiro Takeuchi (NITech/NIMS/RIKEN), Masayuki Karasuyama (NITech/NIMS/JST) IBISML2017-64 |
Large margin metric learning learns the optimal Mahalanobis distance for classification problem based on the margin maxi... [more] | IBISML2017-64 pp.219-226 |
| IE, ITS, ITE-AIT, ITE-HI, ITE-ME, ITE-MMS, ITE-CE [detail] | 2017-02-21 09:00 |
Hokkaido | Hokkaido Univ. | A Comparative Evaluation of Deep Features
-- Classifier-based Learning vs. Distance Metric Learning. -- Shota Horiguchi, Daiki Ikami, Kiyoharu Aizawa (UTokyo) |
The extraction of useful deep features is important for many computer vision tasks. Deep features extracted from classif... [more] | |
| AI | 2015-12-19 10:50 |
Okinawa | A Study of Local Distance Metric Learning and Classifying Method Based on the Local Distances Saito Hiroshi, Mikawa Kenta, Goto Masayuki (Waseda Univ.) AI2015-50 |
The distance metric learning is the approach which enables to acquire a good metric for automatic data classification. I... [more] | AI2015-50 pp.143-148 |
|
| IT | 2015-09-04 10:15 |
Ishikawa | Hakusan Shobutei | Nested Lattice Hashing Scheme for Similarity Search Applications Thanh Xuan Nguyen, Ricardo Antonio Parrao Hernandez, Brian Michael Kurkoski (JAIST) IT2015-37 |
This research targets improving similarity search efficiency using a nested lattice hashing scheme. Similarity search ha... [more] | IT2015-37 pp.19-24 |
| IT | 2014-07-17 10:10 |
Hyogo | Kobe University | Distance Metric Learning with Low Computational Complexity based on Ensemble of Low-dimensional Matrixes Hiroshi Saito, Fumihiro Yamazaki, Kenta Mikawa, Masayuki Goto (Waseda Univ.) IT2014-12 |
The distance metric learning is the approach which enables to acquire a good metric for automatic data classification. I... [more] | IT2014-12 pp.7-12 |
| ET | 2014-06-14 13:40 |
Shizuoka | Shizuoka Univ. (Hamamatsu Campus) | Term co-occurence base analysis of note content student taken in a blended learning environment Minoru Nakayama (Tokyo Inst. of Tech.), Kouichi Mutsuura (Shinshu Univ.), Hiroh Yamamoto (Tokyo Inst. of Tech.) ET2014-14 |
Note contents students taken during a blended learning course were evaluated to develop an appropriate instruction at ... [more] |
ET2014-14 pp.33-38 |
| PRMU, IPSJ-CVIM, MVE [detail] | 2014-01-24 15:30 |
Osaka | People Re-identification with Auxiliary Knowledge Guanwen Zhang, Jien Kato, Yu Wang, Kenji Mase (Nagoya Univ.) PRMU2013-114 MVE2013-55 |
There is an intrinsic issue in multiple-shot person re-identification: only a few training data for learning tasks are ... [more] |
PRMU2013-114 MVE2013-55 pp.251-255 |
|
| PRMU, MI, IE | 2011-05-20 14:00 |
Aichi | Human Re-identification by Non-linear Distance Metric Learning Yoshihisa Ijiri, Shihong Lao (OMRON), Hiroshi Murase (Nagoya Univ.) IE2011-33 PRMU2011-25 MI2011-25 |
To do tracking of a specific person, since a field of view in a camera is limited, the use of multiple surveillance came... [more] | IE2011-33 PRMU2011-25 MI2011-25 pp.139-146 |
|
| NC | 2009-10-24 11:05 |
Saga | Saga University | Learning of a Gibbs distribution from gene configurations in the genetic algorithm Manabu Kitagata, Jun-ichi Inoue (Hokkaido Univ.) NC2009-45 |
We introduce a learning algorithm of Gibbs distributions from training sets which are gene configurations generated by G... [more] | NC2009-45 pp.47-52 |
| SP | 2008-03-20 15:15 |
Tokyo | Univ. Tokyo | [Poster Presentation]
Unsupervised Phoneme Segmentation Using Mahalanobis Distance Yu Qiao, Nobuaki Minematsu (Univ. of Tokyo) SP2007-198 |
One of the fundamental problems in speech engineering is phoneme segmentation. Approaches to phoneme segmentation can be... [more] | SP2007-198 pp.69-74 |
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