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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| MSS, SS | 2025-01-13 10:50 |
Kagoshima | Application of the Statistical Test Rule Induction Method to Classification Problems and Comparisons with the Neural Network Method Ji Kaikuan, Tomoshi Hatakeyama, Tetsuro Saeki (Yamaguchi Univ.), Yuichi Kato (Shimane Univ.) |
(To be available after the conference date) [more] | ||
| IBISML | 2024-12-20 10:30 |
Hokkaido | Lecture room 1, Graduate School of Environmental Science (Primary: On-site, Secondary: Online) |
Training Deep Neural Networks for Fast Data Assimilation Yuta Ono (UTokyo), Yuta Tarumi, Keisuke Fukuda, Shin-ichi Maeda (PFN) |
(To be available after the conference date) [more] | |
| HIP | 2024-12-16 15:00 |
Miyagi | RIEC | Eccentricity-dependent response of internal units in a deep neural network incorporating cortical magnification Shunta Ura, Takahisa M. Sanada (Iwate Prefectural Univ.)  HIP2024-56 |
(To be available after the conference date) [more] | HIP2024-56 pp.24-29 |
| MBE | 2024-12-07 10:45 |
Osaka | KINDAI University | Implementation of Information Relay-and-Gate Function in an Intra-Cortical Visual Prosthesis System
-- Numerical Simulation and Evaluation of a Lateral Geniculate Nucleus Model -- Naonari Onishi, Tomoya Nokura, Ryosuke Okada, Yuki Hayashida (Mie Univ.) MBE2024-19 |
Intracortical visual prostheses for acquired blindness have gained renewed interest. Our group previously developed a sy... [more] | MBE2024-19 pp.14-19 |
| MBE | 2024-12-07 11:10 |
Osaka | KINDAI University | Identification of Spatio-Temporal Filters in the Neural Network Models Trained as Epileptic Electrocorticogram Detectors Daisuke Suekane, Moemi Yamaji, Shinjiro Yamamasu, Yuki Hayashida (Mie Univ.) MBE2024-20 |
Responsive Neuro-stimulation, which detects abnormal brain activity recorded through electrodes placed on the brain surf... [more] | MBE2024-20 pp.20-25 |
| SIS | 2024-12-05 11:00 |
Osaka | Osaka Electro-Communication University (Primary: On-site, Secondary: Online) |
Noise-robust Recommender System Based on Training Sample Confidence Takuto Sugiyama, Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) SIS2024-32 |
In recommender systems, the use of implicit feedback has become common. However, implicit feedback can include interacti... [more] | SIS2024-32 pp.7-12 |
| SIS | 2024-12-05 11:20 |
Osaka | Osaka Electro-Communication University (Primary: On-site, Secondary: Online) |
Two-stage Diversified Recommendation using Communities in Social Media Hiroki Fujiwara, Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) SIS2024-33 |
User recommendation systems on social media platforms play a critical role in discovering new contents and expanding soc... [more] | SIS2024-33 pp.13-18 |
| SIS | 2024-12-05 11:40 |
Osaka | Osaka Electro-Communication University (Primary: On-site, Secondary: Online) |
Learning Region-specific Features and Matching Distributions Across Regions in Geographical Domain Adaptation Takashi Horihata, Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) SIS2024-34 |
Domain adaptation in image recognition has been widely studied as a technique to maintain high accuracy on images with d... [more] | SIS2024-34 pp.19-24 |
| MRIS, ITE-MMS | 2024-12-05 14:20 |
Ehime | Ehime Univ. (CITE) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Holographic memory using complex-amplitude-modulated signal beam Masatoshi Bunsen, Tomohiro Nishimura (Fukuoka Univ.) |
To achieve high-speed and large-capacity holographic memory, complex amplitude modulation, which applies modulation to b... [more] | |
| WBS, ITS, RCC | 2024-12-05 09:50 |
Kagoshima | Kagoshima Prefectural Culture Center (Primary: On-site, Secondary: Online) |
A study on indoor positioning based on neural network by using array antenna Haruki Shimizu, Masahiro Fujii (Utsunomiya Univ.) WBS2024-52 ITS2024-33 RCC2024-57 |
It is known that the fingerprinting method using received signals from array antennas can provide more accurate position... [more] | WBS2024-52 ITS2024-33 RCC2024-57 pp.117-122 |
| PRMU, IPSJ-CVIM, IPSJ-CGVI, IPSJ-DCC | 2024-11-29 11:10 |
Fukui | (Primary: On-site, Secondary: Online) |
Learning Neural Velocity Fields using Edge-based Ray Sampling Sota Ito, Yoshikazu Hayashi (Gifu Univ.), Hiroaki Aizawa (Hiroshima Univ), Kunihito Kato (Gifu Univ.) PRMU2024-10 |
Neural Velocity Fields for 3D Physics Learning from Dynamic Videos (NVFi) enables future frame extrapolation by learning... [more] | PRMU2024-10 pp.13-18 |
| PRMU, IPSJ-CVIM, IPSJ-CGVI, IPSJ-DCC | 2024-11-30 10:15 |
Fukui | (Primary: On-site, Secondary: Online) |
Disentangle Learning for Interactive Semiconductor Inspection Robust to Thin-Film Interference Koki Mitsusada, Koji Kamma, Toshikazu Wada (Wakayama Univ.), Yasuhiro Hamada, Yoshinori Shimada, Takeshi Noguchi, Toshiyuki Okayama (Advanced System Solutions Co., Ltd.) PRMU2024-25 |
In the semiconductor wafer inspection process, an intensity difference-based method is widely used, in which defects are... [more] | PRMU2024-25 pp.93-98 |
| PRMU, IPSJ-CVIM, IPSJ-CGVI, IPSJ-DCC | 2024-11-30 14:40 |
Fukui | (Primary: On-site, Secondary: Online) |
Analysis of Latent Features from Adversarial Examples on Perception and Reconstruction Takumi Maeda (Koshi High School), Soichiro Kumano, Toshihiko Yamasaki (UTokyo) PRMU2024-28 |
In image recognition and reconstruction tasks using autoencoders, it is known that deep features through models differ. ... [more] | PRMU2024-28 pp.101-104 |
| EMT, IEE-EMT | 2024-11-26 15:55 |
Shizuoka | Shizuoka Convestion & Arts Center | On applying transfer learning into the neural network method for electromagnetic analysis Kazuhiro Fujita (Saitama IT) EMT2024-61 |
The author has been working on the development of the neural network methods for electromagnetic analysis. In this repor... [more] | EMT2024-61 pp.13-16 |
| EMT, IEE-EMT | 2024-11-27 10:50 |
Shizuoka | Shizuoka Convestion & Arts Center | [Invited Lecture]
An attempt for applying Physics-informed Neural Network to reconstruction of a dielectric cylinder from scattered waves Kenichi Ishida, Tsuyoshi Matsuoka (Kyushu Sangyo Univ.) EMT2024-71 |
Inverse scattering problems for reconstructing a dielectric object from measured scattered waves are often reduced to op... [more] | EMT2024-71 pp.66-71 |
| EMT, IEE-EMT | 2024-11-28 10:25 |
Shizuoka | Shizuoka Convestion & Arts Center | Proposal of Extended Liquid Time-Constant Neural Networks to Solve Partial Differential Equations Justin Jun Wilkins, Yukihisa Suzuki (Tokyo Metropolitan Univ.) EMT2024-77 |
The purpose of this study is to develop a machine learning model using deep learning as a surrogate model for analysing ... [more] | EMT2024-77 pp.96-101 |
| QIT (2nd) |
2024-11-26 13:20 |
Kagawa | Sunport Hall Takamatsu | [Poster Presentation]
Performance Evaluation of Surface Code Decoders Using Machine Learning under Non-stationary Noise Toshihide Hinokuma (Kyushu Univ) |
The surface code decoder normally treats errors as a stationary process and estimates recovery operations from error obs... [more] | |
| QIT (2nd) |
2024-11-26 13:20 |
Kagawa | Sunport Hall Takamatsu | [Poster Presentation]
Feature extraction by photon-based quantum extreme learning machine
-- Analysis of non-classical high-dimensional nonlinear projection -- Akio Yoshizawa (AIST) |
Extreme learning machine (ELM) is a feedforward neural network with a single or multiple hidden layers. Unlike the convo... [more] | |
| UWT (2nd) |
2024-11-19 15:00 |
Kagoshima | Space Division Multiplexing Transmission and Demodulation Scheme for CSK-UWOCC Using LEDs Yuta Furukawa, Yuki Sasaki (Tokyo Univ. of Science), Hisano Daisuke (Osaka Univ), Yu Nakayama (Tokyo Univ. of Agriculture and Technology), Kazuki Maruta (Tokyo Univ. of Science) |
Thegrowingdemandforhigh-capacity communication systems has highlighted Underwater Optical Camera Communication (UWOCC) a... [more] | ||
| PN | 2024-11-18 13:55 |
Oita | (Primary: On-site, Secondary: Online) |
Sequence Estimation Method to Alleviate Spectrum Narrowing Reiji Higuchi, Taisei Sekizuka, Kazato Satake, Takuma Kuno (Nagoya Univ.), Yojiro Mori (Toyota Tech. Inst.), Hiroshi Hasegawa (Nagoya Univ.) PN2024-29 |
To efficiently increase network capacity, it is crucial to accelerate signal rates per wavelength and densify wavelength... [more] | PN2024-29 pp.12-16 |
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