Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
ICSS, IPSJ-SPT |
2024-03-22 10:55 |
Okinawa |
OIST (Primary: On-site, Secondary: Online) |
Improved signature-embedding techniques against backdoor attacks on DNN models Akira Fujimoto, Yuntao Wang, Atsuko Miyaji (OU) ICSS2023-87 |
In recent years, machine learning, particularly deep learning, has made remarkable strides, and has great impact on our ... [more] |
ICSS2023-87 pp.129-136 |
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 |
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] |
2024-03-15 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 |
IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-15 16:10 |
Okinawa |
Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
Study of Sperm Quality Assessment from Video Data Sigit Adinugroho, Atsushi Nakazawa (Okayama University) IMQ2023-91 IE2023-146 MVE2023-120 |
Human sperm quality assessment is necessary for a successful assisted reproduction program. Current assessment still rel... [more] |
IMQ2023-91 IE2023-146 MVE2023-120 pp.420-424 |
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, Masao Masugi, Kenshi Saho (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) |
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 |
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 |
PRMU, IBISML, IPSJ-CVIM |
2024-03-03 15:24 |
Hiroshima |
Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
PRMU2023-62 |
(To be available after the conference date) [more] |
PRMU2023-62 pp.64-69 |
MI |
2024-03-03 14:30 |
Okinawa |
OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Invited Lecture]
Latest Research Trends 2023: Machine Learning for Medical Image Processing Fukashi Yamazaki (Canon) MI2023-48 |
In this paper, we overview the outlines of MICCAI 2023’s main conference sessions and satellite workshops. Several inter... [more] |
MI2023-48 pp.53-55 |
PRMU, IBISML, IPSJ-CVIM |
2024-03-04 09:00 |
Hiroshima |
Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
PRMU2023-64 |
(To be available after the conference date) [more] |
PRMU2023-64 pp.76-81 |
PRMU, IBISML, IPSJ-CVIM |
2024-03-04 09:24 |
Hiroshima |
Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
PRMU2023-66 |
(To be available after the conference date) [more] |
PRMU2023-66 pp.88-93 |
PRMU, IBISML, IPSJ-CVIM |
2024-03-04 11:16 |
Hiroshima |
Hiroshima Univ. Higashi-Hiroshima campus (Primary: On-site, Secondary: Online) |
PRMU2023-73 |
(To be available after the conference date) [more] |
PRMU2023-73 pp.128-133 |
HCS |
2024-03-02 12:05 |
Shizuoka |
Tokoha University(Shizuoka-Kusanagi Campus) |
Estimation of willingness to participate in other's conversation by using deep learning of facial expression measurements Kohei Yamamoto, Jiro Okuda (Kyoto Sangyo Univ.) HCS2023-92 |
In recent years, there has been much interest in developing agents that can join conversations among multiple people and... [more] |
HCS2023-92 pp.25-30 |
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 |
EST |
2024-01-26 13:50 |
Kyoto |
Kyoto University ROHM Plaza (Primary: On-site, Secondary: Online) |
A Study on Three-dimensional Electromagnetic Field Simulation Using Physics-Informed Neural Network Method Kazuhiro Fujita (Saitama IT) EST2023-118 |
A neural network method based on physical laws in electromagnetics has been developed so far. However, its applicability... [more] |
EST2023-118 pp.108-111 |
NC, MBE, NLP, MICT (Joint) [detail] |
2024-01-25 09:00 |
Tokushima |
Naruto University of Education |
The Relationship Between Metrics in the Latent Variable Space and Image Classification Performance Haruki Wakasa, Kenya Jin'no (Tokyo City Univ.) NLP2023-99 MICT2023-54 MBE2023-45 |
In recent years, models based on convolutional neural networks (CNNs) have exhibited high performance in image classific... [more] |
NLP2023-99 MICT2023-54 MBE2023-45 pp.78-81 |