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All Technical Committee Conferences (Searched in: All Years)
| 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, Hirotada Honda, Shugo Nakamura, Takashi Sano (Toyo Univ) |
(To be available after the conference date) [more] | |
| 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 |
| 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 |
| 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 |
| 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 |
| SeMI | 2024-01-18 13:30 |
Yamanashi | Raki House Kaiji | Enhancing Human Skeleton Estimation with Multi-Frame mmWave Radar Point Cloud-based Method Xintong Shi, Tomoaki Ohtsuki (Keio Univ.) SeMI2023-52 |
Millimeter-Wave (mmWave) radar-based skeleton estimation has emerged as a focal point in the realm of human motion analy... [more] | SeMI2023-52 pp.18-21 |
| NLP | 2023-11-28 13:50 |
Okinawa | Nago city commerce and industry association | Considerations on the distribution of latent variables in CNNs Mizuki Dai, Kenya Jin'no (Tokyo City Univ.) NLP2023-65 |
Abstract Fully comprehending the output decision mechanisms of neural networks is a critical challenge. This article foc... [more] | NLP2023-65 pp.31-34 |
| SCE | 2023-10-31 10:00 |
Miyagi | RIEC, Tohoku Univ. (Primary: On-site, Secondary: Online) |
Design of a Modularized Circuits Library for Binary Convolutional Neural Network Accelerator using Single Flux Quantum Circuits Zeyu Han, Zongyuan Li, Yuki Yamanashi, Nobuyuki Yoshikawa (Yokohama National Univ.) SCE2023-17 |
To implement a binary neural network (BNN) based on SFQ circuits, we designed a modularized circuits library based on th... [more] | SCE2023-17 pp.26-31 |
| BioX | 2023-10-12 15:25 |
Okinawa | Nobumoto Ohama Memorial Hall | A Study on Ear Acoustic Personal Authentication System Using Domain Transformation for Numerical Analysis Data Masafumi Morimoto (Kansai Univ.), Shunsuke Kita (ORIST), Yoshinobu Kajikawa (Kansai Univ.) BioX2023-60 |
We propose a new personal authentication system using ear pinna transfer functions. This proposed method is constructe... [more] |
BioX2023-60 pp.12-15 |
| EMCJ, IEE-EMC, IEE-SPC | 2023-05-12 13:15 |
Okinawa | (Primary: On-site, Secondary: Online) |
Evaluating Transmission Efficiency Impact on Screen Reconstruction Accuracy for High-Resolution Displays Taiki Kitazawa, Yuichi Hayashi (NAIST) EMCJ2023-6 |
In TEMPEST attacks targeting high-resolution displays with divided screens, reconstructing screen information proves dif... [more] | EMCJ2023-6 pp.1-6 |
| NLP, MSS | 2023-03-17 16:05 |
Nagasaki | (Primary: On-site, Secondary: Online) |
Lightweighting Noisy Student Semi-Supervised Learning by Applying MobileNet Yuga Morishima, Hidehiro Nakano (Tokyo City Univ.) MSS2022-108 NLP2022-153 |
Recently, Convolutional Neural Networks (CNNs) have attracted much attention in various fields such as image classificat... [more] | MSS2022-108 NLP2022-153 pp.220-224 |
| MI | 2023-03-06 13:15 |
Okinawa | OKINAWA SEINENKAIKAN (Primary: On-site, Secondary: Online) |
[Short Paper]
Improvement of Small Organ Accuracy in Multi-Organ Segmentation of Abdominal CT Images Using 2.5D Deformable Convolutional CNN Yuya Okumura, Hiroyuki Kudo, Hotaka Takizawa (Univ of Tsukuba) MI2022-80 |
In multi-organ segmentation of abdominal CT images using deep learning, small organs such as the pancreas are difficult ... [more] | MI2022-80 pp.38-39 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 11:15 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
Dynamic Weight Scheduling for Long-tailed Visual Recognition Xinyuan Li (Ritsumeikan Univ.), Yu Wang (Hitotsubashi Univ.), Jien Kato (Ritsumeikan Univ.) PRMU2022-78 IBISML2022-85 |
For long-tailed image recognition tasks, re-weighting is effective to alleviate data imbalance by assigning higher weigh... [more] | PRMU2022-78 IBISML2022-85 pp.107-110 |
| CAS, CS | 2023-03-01 09:30 |
Fukuoka | Kitakyushu International Conference Center (Primary: On-site, Secondary: Online) |
Modification and Comparison of Learning Sudoku with Convolutional Networks Koichiro Ishii, Hiroshi Tamura (Chuo Univ.) CAS2022-96 CS2022-73 |
Sudoku is a logic puzzle in which the number between 1 and 9 is to fill in the boxes of the 9x9 grid by using the number... [more] | CAS2022-96 CS2022-73 pp.1-5 |
| ICTSSL, CAS | 2023-01-26 11:15 |
Tokyo | TBD (Primary: On-site, Secondary: Online) |
On Image Recognition Neural Networks and Polynomial Approximation of Images Jiahang Chang, Kazuya Ozawa, Hideaki Okazaki (SIT) CAS2022-66 ICTSSL2022-30 |
In this report, we present a convolutional neural network that we have built ourselves for our research. Then, we discus... [more] | CAS2022-66 ICTSSL2022-30 pp.23-27 |
| IBISML | 2022-12-23 11:10 |
Kyoto | Kyoto University (Primary: On-site, Secondary: Online) |
Enhancement of Audio Signals Using Learning from Positive and Unlabelled Data Nobutaka Ito, Masashi Sugiyama (UTokyo) IBISML2022-56 |
Audio signal enhancement (SE) is the task of extracting a desired class of sounds (a “signal”) from an observed sound mi... [more] | IBISML2022-56 pp.94-100 |
| HCGSYMPO (2nd) |
2022-12-14 - 2022-12-16 |
Kagawa | Onsite (Sunport Takamatsu) and Online (Primary: On-site, Secondary: Online) |
Analyzing and Recognizing Synergetic Functions between Head Movements and Facial Expressions in Conversations Mai Imamura, Kazuki Takeda (YNU), Shiro Kumano (NTT), Kazuhiro Otsuka (YNU) |
In this paper, we propose machine-learning models for recognizing the synergetic functions between facial expressions an... [more] | |
| MBE, NC | 2022-12-03 11:00 |
Osaka | Osaka Electro-Communication University | Image Classification Using Gabor Filters as Preprocessing for CNNs Akito Morita, Hirotsugu Okuno (OIT) MBE2022-32 NC2022-54 |
Image preprocessing is a promising approach to improve accuracy in image classification using convolutional neural netwo... [more] | MBE2022-32 NC2022-54 pp.43-46 |
| CCS, NLP | 2022-06-09 14:15 |
Osaka | (Primary: On-site, Secondary: Online) |
Improvement of Recognition Accuracy by Sequential Execution of Unsupervised Learning and Semi-supervised Learning Hiroki Murakami, Hidehiro Nakano (Tokyo City Univ.) NLP2022-4 CCS2022-4 |
In this study, we propose a sequential learning method that improves recognition accuracy by alternately utilizing the k... [more] | NLP2022-4 CCS2022-4 pp.17-22 |
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