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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| RCC, ISEC, IT, WBS | 2024-03-13 15:05 |
Osaka | Osaka Univ. (Suita Campus) | Efficient Replay Data Selection in Continual Federated Learning Model Yuto Kitano (Kobe Univ), Lihua Wang (NICT), Seiichi Ozawa (Kobe Univ)  IT2023-96 ISEC2023-95 WBS2023-84 RCC2023-78 |
In this study, we propose a continual federated learning that can continuously learn distributed data generated daily by... [more] | IT2023-96 ISEC2023-95 WBS2023-84 RCC2023-78 pp.135-141 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-13 13:20 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
[Invited Talk]
The Past, Current and Future of Fashion Image Retrieval: Toward a User-Centered Orientation Ling Xiao (UTokyo) IMQ2023-28 IE2023-83 MVE2023-57 |
Fashion image retrieval (FIR) plays a pivotal role in enhancing the online shopping experience on retail and e-commerce ... [more] | IMQ2023-28 IE2023-83 MVE2023-57 pp.87-89 |
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-03-01 10:40 |
Okinawa | (Primary: On-site, Secondary: Online) |
An Investigation into Weighting Strategies for Model Averaging in Continual Learning for Automatic Speech Recognition Kentaro Shinayama, Hiroshi Sato, Tomoharu Iwata, Takeshi Mori, Taichi Asami (NTT) EA2023-105 SIP2023-152 SP2023-87 |
In recent years, the application scope of speech recognition AI has expanded, enabling the acquisition of diverse data d... [more] | EA2023-105 SIP2023-152 SP2023-87 pp.262-267 |
| ITS, IE, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2024-02-19 11:00 |
Hokkaido | Hokkaido Univ. | Improving Adversarial Robustness in Continual Learning Koki Mukai, Soichiro Kumano (UTokyo), Nicolas Michel (UGE/CNRS/LIGM), Ling Xiao, Toshihiko Yamasaki (UTokyo) ITS2023-48 IE2023-37 |
The goal of continual learning is to prevent catastrophic forgetting. However, few studies have simultaneously considere... [more] | ITS2023-48 IE2023-37 pp.13-18 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-03 17:00 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Continual learning combining Replay and Parameter Isolation Methods Ryota Adachi, Toshikazu Wada (Wakayama Univ.) PRMU2022-121 IBISML2022-128 |
Deep Neural Networks (DNN) are used for various tasks such as image classification, but when a new task is trained on a ... [more] | PRMU2022-121 IBISML2022-128 pp.335-340 |
| RCS, SR, SRW (Joint) |
2023-03-01 10:00 |
Tokyo | Tokyo Institute of Technology, and Online (Primary: On-site, Secondary: Online) |
Continual Learning and Deep Transfer Learning Based CSI Feedback in FDD Massive MIMO Systems Mayuko Inoue, Tomoaki Ohtsuki (Keio Univ.) RCS2022-251 |
In frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO), the downlink channel state informat... [more] | RCS2022-251 pp.25-30 |
| NC, IBISML, IPSJ-BIO, IPSJ-MPS [detail] | 2022-06-27 14:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
AI knowledge forgetting based on the importance of model parameters Tomoya Yamashita, Masanori Yamada (NTT) NC2022-3 IBISML2022-3 |
The accuracy of Deep Learning has been greatly improved by the progress of research in computer technology and Deep Lear... [more] | NC2022-3 IBISML2022-3 pp.14-19 |
| PRMU, IPSJ-CVIM | 2022-03-10 09:30 |
Online | Online | PRMU2021-62 |
no English abstract [more] | PRMU2021-62 pp.13-18 |
| MI | 2022-01-26 11:31 |
Online | Online | Investigation of post implementation training for medical image reading support systems Chisako Muramatsu (Shiga Univ), Mizuho Nishio (Kobe Univ), Masahiro Yakami (Kyoto Univ), Takeshi Kubo (Tenri Hospital), Mikinao Ooiwa (Nagoya Medical Center), Hiroshi Fujita (Gifu Univ) MI2021-58 |
It is desirable to have robust image interpretation support systems that can obtain the equivalent accuracy for images a... [more] | MI2021-58 pp.55-58 |
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