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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| PN | 2024-03-15 11:40 |
Kagoshima | (Primary: On-site, Secondary: Online) |
[Invited Talk]
Machine learning techniques for monitoring photonic networks Takahito Tanimura (Hitachi)  PN2023-83 |
Recent advancements in machine learning technologies, particularly focusing on deep learning, and their application to p... [more] | PN2023-83 pp.74-78 |
| CAS, CS | 2024-03-15 14:20 |
Okinawa | Recoloring aware Countermeasure against Adversarial Examples Chisei Ishida, Ryo Kumagai, Shu Takemoto, Yusuke Nozaki, Masaya Yoshikawa (Meijo Univ.) CAS2023-134 CS2023-127 |
Adversarial Examples(AEs) which cause artificial intelligence (AI) to make a false prediction by embedded slight perturb... [more] | CAS2023-134 CS2023-127 pp.128-133 |
|
| 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 |
|
| KBSE | 2024-03-15 14:50 |
Okinawa | Okinawa Prefectual General Welfare Center (Primary: On-site, Secondary: Online) |
Learning data creation support tool for learning program defects using images Kazuhiko Ogawa, Takako Nakatani (OUJ) KBSE2023-89 |
We have developed CNN-BI system that learns and infers defects from the images of programs. This paper introduces a tool... [more] | KBSE2023-89 pp.132-137 |
| RCC, ISEC, IT, WBS | 2024-03-14 10:20 |
Osaka | Osaka Univ. (Suita Campus) | Improving classification accuracy of imaged malware through data expansion Kaoru Yokobori, Hiroki Tanioka, Masahiko Sano, Kenji Matsuura, Tetsushi Ueta (Tokushima Univ.) IT2023-115 ISEC2023-114 WBS2023-103 RCC2023-97 |
Although malware-based attacks have existed for years, malware infections increased in 2019 and 2020. One of the reaso... [more] |
IT2023-115 ISEC2023-114 WBS2023-103 RCC2023-97 pp.259-264 |
| 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 |
| RCS, SR, SRW (Joint) |
2024-03-13 16:40 |
Tokyo | The University of Tokyo (Hongo Campus), and online (Primary: On-site, Secondary: Online) |
A Plug-and-Play Module for Enhancing Fault-Tolerant Distributed Inference Based on Gaussian Dropout Hou Zhangcheng, Ohtsuki Tomoaki (KU) RCS2023-267 |
Distributed inference (DI) in the Internet of Things (IoT) is becoming increasingly important as the demand for AI appli... [more] | RCS2023-267 pp.77-82 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-14 15:20 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
Efficient regularizer for 4D light field image denoising based on graph-learning Rino Yoshida (TUS), Kazuya Kodama (NII), Gene Cheung (York Univ.), Takayuki Hamamoto (TUS) IMQ2023-56 IE2023-111 MVE2023-85 |
Advanced 3D visual media as promising technology often require 4D light fields composed of dense multi-view images for a... [more] | IMQ2023-56 IE2023-111 MVE2023-85 pp.235-240 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-14 16:00 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
Study of Feature Visualization of Running Motion from RGB Videos Using Spatial Temporal Graph Convolutional Networks and Deep Metric Learning Haruya Tanaka, Chanjin Seo (Waseda Univ.), Hiroyuki Ogata (Seikei Univ.), Jun Ohya (Waseda Univ.) IMQ2023-58 IE2023-113 MVE2023-87 |
In recent years, the running population has been increasing, and demand for coaching systems for amateur runners is expe... [more] | IMQ2023-58 IE2023-113 MVE2023-87 pp.246-251 |
| RCS, SR, SRW (Joint) |
2024-03-15 16:15 |
Tokyo | The University of Tokyo (Hongo Campus), and online (Primary: On-site, Secondary: Online) |
Study on Small Cell ON/OFF Control Using Different Frequency Cell Information Takaharu Kobayashi, Takashi Dateki (Fujitsu) RCS2023-292 |
In this paper, we propose small cell ON/OFF control without using UE position information and information on the proximi... [more] | RCS2023-292 pp.176-181 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-15 09:50 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
IMQ2023-68 IE2023-123 MVE2023-97 |
We propose a simultaneous method of multimodal graph signal denoising and graph learning. Since sensor networks distribu... [more] | IMQ2023-68 IE2023-123 MVE2023-97 pp.301-306 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-15 10:30 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
A Point Cloud Downsampling Method Considering Local Features for 3D Object Classification Ryota Sugimoto, Kenji Kanai, Shiori Maki, Jiro Katto (Waseda Univ.) IMQ2023-70 IE2023-125 MVE2023-99 |
In recent years, use of point cloud data has been considered for 3D spatial recognition. To reduce processing load cause... [more] | IMQ2023-70 IE2023-125 MVE2023-99 pp.313-318 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-15 13:50 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
IMQ2023-87 IE2023-142 MVE2023-116 |
This paper introduces physics-inspired synthesized underwater image dataset (PHISWID). Deep learning approaches to unde... [more] |
IMQ2023-87 IE2023-142 MVE2023-116 pp.396-401 |
| ITS, IEE-ITS | 2024-03-11 14:00 |
Shiga | BKC, Ritsumeikan Univ. (Primary: On-site, Secondary: Online) |
Doppler radar-based recognition of bicycle motions Ryoya Hayashi, Kenshi Saho, Masao Masugi (Ritsumeikan Univ.) ITS2023-80 |
In this report, we present the results of an experiment in which a Doppler radar-based method was used to detect four be... [more] | ITS2023-80 pp.7-10 |
| NC, MBE (Joint) |
2024-03-12 14:45 |
Tokyo | The Univ. of Tokyo (Primary: On-site, Secondary: Online) |
Investigating the Effect of Skip Connection on Learning Dynamics in the Initial Learning Process of Deep Neural Networks 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 |
| SS | 2024-03-07 17:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
For evaluating the effectiveness of CodeT5 transfer learning in refactoring recommendations. Yuto Nakajima, Kenji Fujiwara (Tokyo City University) SS2023-62 |
Refactoring is "the process of restructuring the internal architecture of software to make it easier to understand and m... [more] | SS2023-62 pp.79-84 |
| 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 |
| PRMU, IBISML, IPSJ-CVIM | 2024-03-03 09:24 |
Hiroshima | Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
Cardiac Detection in Non-Contrast CT and Application to Calcium Scoring Tetsuya Asakawa, Hiroki Shinoda (TUT), Takuya Togawa, Kazuki Shimizu (THC), Masaki Aono (TUT) PRMU2023-59 |
Coronary artery disease, one of the major causes of death in Japan, is said to be related to coronary artery calcifica- ... [more] | PRMU2023-59 pp.47-52 |
| MI | 2024-03-03 09:53 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Deep Learning based Objective Microscopic Agglutination Test Risa Nakano, Yuji Oyamada (Tottori Univ.), Ryo Ozuru (Fukuoka Univ.) MI2023-34 |
This paper aims to achieve objective justification of decision criteria in Microscopic Agglutination Test (MAT), which i... [more] | MI2023-34 pp.15-18 |
| MI | 2024-03-03 10:17 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Electric field regression from head MR image by transformers for TMS Toyohiro Maki, Tatsuya Yokota, Akimasa Hirata, Hidekata Hontani (NIT) MI2023-36 |
Transcranial Magnetic Stimulation (TMS) is a non-invasive stimulation method by electric field induced by a coil placed ... [more] | MI2023-36 pp.21-24 |
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