Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
PRMU, IPSJ-CVIM |
2024-05-16 09:45 |
Tokyo |
(Primary: On-site, Secondary: Online) |
Development and evaluation of a video segmentation model using differences between frames Sota Kawamura, Shugo Nakamura, Hirotada Honda, Takashi Sano (Toyo Univ) |
(To be available after the conference date) [more] |
|
NLP |
2024-05-10 10:30 |
Kagawa |
Kagawa Prefecture Social Welfare Center |
Federated Learning Algorithms based on Decentralized Spanning Tree Generation and Step-by-Step Consensus Yuki Mori, Tatsuya Kayatani, Tsuyoshi Migita, Norikazu Takahashi (Okayama Univ.) |
(To be available after the conference date) [more] |
|
NLP |
2024-05-10 11:20 |
Kagawa |
Kagawa Prefecture Social Welfare Center |
Lossless Color Image Compression Based on Colorization by Cellular Neural Networks Shungo Saizuka, Seiya Kushi, Tasuku Kuroda (Chukyo Univ.), Tsuyoshi Otake (Tamagawa Univ.), Hisashi Aomori (Chukyo Univ.) |
(To be available after the conference date) [more] |
|
CCS |
2024-03-27 14:00 |
Hokkaido |
RUSUTSU RESORT |
Evaluation of recurrent neural network training using multi-phase quantization optimizer Hiiro Yamazaki, Itsuki Akeno, Koki Nobori, Tetsuya Asai, Kota Ando (Hokkaido Univ.) CCS2023-44 |
In this research, we apply "Holmes", an optimizer dedicated to edge training of neural networks, to recurrent neural net... [more] |
CCS2023-44 pp.30-35 |
ICSS, IPSJ-SPT |
2024-03-22 14:55 |
Okinawa |
OIST (Primary: On-site, Secondary: Online) |
Adversarial Examples with Missing Perturbation Using Laser Irradiation Daisuke Kosuge, Hayato Watanabe, Taiga Manabe, Yoshihisa Takayama, Toshihiro Ohigashi (Tokai Univ.) ICSS2023-97 |
In recent years, neural networks have made remarkable progress in the field of image processing and other areas, and the... [more] |
ICSS2023-97 pp.201-207 |
AP |
2024-03-14 10:25 |
Fukui |
UNIVERSITY OF FUKUI (Primary: On-site, Secondary: Online) |
Direction of arrival estimation using neural networks and Uniform Cross Array for LoS-MIMO transmission Motoshi Tawada, Yoshichika Ohta (SoftBank) AP2023-202 |
The feeder link between the fixed ground station and the HAPS requires high capacity to accommodate the traffic of termi... [more] |
AP2023-202 pp.7-10 |
AP |
2024-03-15 10:25 |
Fukui |
UNIVERSITY OF FUKUI (Primary: On-site, Secondary: Online) |
A Study on Path loss characteristics estimation methods considering geographical conditions for designing narrowband DR-IoT communication system Takato Ikegame, Naoki Ikeda, Motonari Imai, Tetsushi Ikegami (Meiji Univ.), Mineo Takai (Osaka Univ.), Susumu Ishihara (Shizuoka Univ.), Arata Kato, Shugo Kajita (STE) AP2023-212 |
A versatile variable-range IoT communication system using the VHF-High band, Diversified-Range IoT (DR-IoT) is being con... [more] |
AP2023-212 pp.63-67 |
CAS, CS |
2024-03-15 14:45 |
Okinawa |
|
Exploring Uniform Convergence in Neural Networks and its Implication on Generalization Error Zong Xianzhe, Hiroshi Tamura (CHUO Univ.) CAS2023-135 CS2023-128 |
Uniform Convergence, a well-established framework for evaluating generalization in traditional Machine Learning, frequen... [more] |
CAS2023-135 CS2023-128 pp.134-139 |
RCC, ISEC, IT, WBS |
2024-03-14 15:30 |
Osaka |
Osaka Univ. (Suita Campus) |
Phishing Detection Method Based on Machine Learning Using DNS Graph Yuki Ishida, Syota Nihei, Junko Sato, Atsushi Waseda, Masaki Hanada (Tokyo Univ. of Information Sciences) IT2023-129 ISEC2023-128 WBS2023-117 RCC2023-111 |
Recently, phishing scams have been on the rise, the need for effective defense methods against this phishing scams.
A b... [more] |
IT2023-129 ISEC2023-128 WBS2023-117 RCC2023-111 pp.337-342 |
RCC, ISEC, IT, WBS |
2024-03-14 16:35 |
Osaka |
Osaka Univ. (Suita Campus) |
Construction of an MDL Estimator with Tight Risk Bound in Simple ReLU Networks Yoshinari Takeishi, Jun'ichi Takeuchi (Kyushu Univ.) IT2023-134 ISEC2023-133 WBS2023-122 RCC2023-116 |
We consider the problem of estimating the parameters of the final layer in two-layer neural networks with ReLU activatio... [more] |
IT2023-134 ISEC2023-133 WBS2023-122 RCC2023-116 pp.368-373 |
RCS, SR, SRW (Joint) |
2024-03-13 16:15 |
Tokyo |
The University of Tokyo (Hongo Campus), and online (Primary: On-site, Secondary: Online) |
DOA Estimation Improvement Through Angle-Range-Reduced DNNs Specialized in Narrow DOA Range Daniel Akira Ando, Toshihiko Nishimura, Takanori Sato, Takeo Ohgane, Yasutaka Ogawa (Hokkaido Univ.), Junichiro Hagiwara (Mukogawa Women's Univ.) RCS2023-266 |
In this work, we propose a strategy based on deep neural networks (DNNs) intended to support our past DNN method for dir... [more] |
RCS2023-266 pp.71-76 |
NC, MBE (Joint) |
2024-03-12 14:45 |
Tokyo |
The Univ. of Tokyo (Primary: On-site, Secondary: Online) |
Visualization of the learning process of ResNet revealing its learning dynamics Ryodo Yuge, Takashi Shinozaki (Kindai Univ.) NC2023-59 |
We visualize the impact of skip connections, a key element in residual networks (ResNet), and visualize its impact on th... [more] |
NC2023-59 p.94 |
PRMU, IBISML, IPSJ-CVIM |
2024-03-03 09:00 |
Hiroshima |
Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Analysis of the Impact of Different Resolutions and Datasets on the Architecture Searched with PC-DARTS Kaisei Hara (Nagaoka Univ. of Technology/AIST), Kazuki Hemmi (Univ. of Tsukuba/AIST), Masaki Onisi (AIST/Univ. of Tsukuba) PRMU2023-57 |
In deep learning, image resolution is crucial to improve accuracy and generalizability. However, the research on the spe... [more] |
PRMU2023-57 pp.35-40 |
EMM |
2024-03-02 16:20 |
Overseas |
Day1:JEJU TECHNOPARK, Day2:JEJU Business Agency |
[Fellow Memorial Lecture]
Application of associative memory models to watermarking models Masaki Kawamura (Yamaguchi Univ.) EMM2023-93 |
We proposed a new method called the associative watermarking method, which is an extension of the zero-watermarking meth... [more] |
EMM2023-93 pp.23-27 |
AI |
2024-03-01 13:40 |
Aichi |
Room0221, Bldg.2-C, Nagoya Institute of Technology |
Applying Graph Neural Networks and Reinforcement Learning to the Multiple Depot-Multiple Traveling Salesman Problem Dongyeop Kim, Toshihiro Matsui (NITech) AI2023-39 |
In this study, we introduce a method combining Graph Neural Networks (GNN) and reinforcement learning for the Multiple D... [more] |
AI2023-39 pp.13-18 |
AI |
2024-03-01 14:40 |
Aichi |
Room0221, Bldg.2-C, Nagoya Institute of Technology |
Request span extraction from dialog with Heterogeneous Graph Attention Networks Naoki Mizumoto, Katsuhide Fujita (TUAT) AI2023-41 |
In this study, we formulate the problem of extracting user requests from the dialogue history as a ``span extraction pro... [more] |
AI2023-41 pp.25-30 |
DC |
2024-02-28 13:40 |
Tokyo |
Kikai-Shinko-Kaikan Bldg. |
Test Point Selection Method for Multi-Cycle BIST Using Deep Reinforcement Learning Kohei Shiotani, Tatsuya Nishikawa, Shaoqi Wei, Senling Wang, Hiroshi Kai, Yoshinobu Higami, Hiroshi Takahashi (Ehime Univ.) DC2023-98 |
Multi-cycle BIST is a test method that performs multiple captures for each scan pattern, proving effective in reducing t... [more] |
DC2023-98 pp.23-28 |
EID, ITE-IDY, IEE-EDD, SID-JC, IEIJ-SSL [detail] |
2024-01-25 13:15 |
Kyoto |
(Primary: On-site, Secondary: Online) |
[Poster Presentation]
Reproduction of changes in membrane potential of neurons by synaptic devices using memristors Kenta Yachida, Yoshiya Abe, Kazuki Sawai (Ryukoku Univ.), Tokiyoshi Matsuda (Kindai Univ./Ryukoku Univ.), Hidenori Kawanishi (Ryukoku Univ.), Mutsumi Kimura (Ryukoku Univ./NAIST) EID2023-4 |
We attempted to replicate the changes in the membrane potential of neurons using thin-film neuromorphic devices that int... [more] |
EID2023-4 pp.9-12 |
PRMU, MVE, VRSJ-SIG-MR, IPSJ-CVIM |
2024-01-26 15:46 |
Kanagawa |
Keio Univ. (Hiyoshi Campus) |
PRMU2023-48 |
In the realm of autonomous driving, end-to-end models (E2EDMs) have gained prominence due to their high predictive accur... [more] |
PRMU2023-48 pp.46-49 |
ICTSSL, CAS |
2024-01-25 11:45 |
Kanagawa |
(Primary: On-site, Secondary: Online) |
Comparison of transfer learning and fine tuning Ohata Shunsuke, Okazaki Hideaki (SIT) CAS2023-88 ICTSSL2023-41 |
This report examines the principal image recognition methods. First, we show the experimental results of image recogniti... [more] |
CAS2023-88 ICTSSL2023-41 pp.31-33 |