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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| IT, EMM | 2024-05-31 09:30 |
Chiba | Chiba University (Nishi-Chiba Campus) | A Reversible Image Processing Method Using Data Hiding for OpenEXR Images Anna Yamaguchi, Shoko Imaizumi (Chiba Univ.) |
(To be available after the conference date) [more] | |
| OPE, LQE, OFT, OCS | 2024-05-17 14:35 |
Online | Online | [Invited Talk]
Report on OFC2024
-- optical transceivers -- Shota Ishimura (KDDI Research) |
(To be available after the conference date) [more] | |
| ICM | 2024-03-22 09:50 |
Okinawa | Okinawa Prefectural Museum and Art Museum (Primary: On-site, Secondary: Online) |
Proposal for Parallel Code Generation and Dynamic Distributed-Cluster Selection in Ray Application Rina Ueno, Nao Nisijima (Hitachi)  ICM2023-53 |
In data analysis systems, a distributed processing infrastructure can be used to increase speed through parallelization ... [more] | ICM2023-53 pp.47-50 |
| RCC, ISEC, IT, WBS | 2024-03-13 14:15 |
Osaka | Osaka Univ. (Suita Campus) | Data processing methods for high-performance Privacy-Preserving Machine Learning Tatsuhiro Yamatsuki (Osaka Univ.), Atsuko Miyaji (Osaka Univ./JAIST) IT2023-94 ISEC2023-93 WBS2023-82 RCC2023-76 |
Currently, attempts are being made in various fields to solve problems by utilizing big data. However, privacy protectio... [more] | IT2023-94 ISEC2023-93 WBS2023-82 RCC2023-76 pp.118-126 |
| NLP, MSS | 2024-03-13 17:20 |
Misc. | Kikai-Shinko-Kaikan Bldg. | Application of Data Augmentation in Japanese Foundation Models Kazuki Era, Hidehiro Nakano (Tokyo City Univ.) MSS2023-84 NLP2023-136 |
One of the recent topics is data augmentation. Data augmentation is a method of augmenting training data to improve the ... [more] | MSS2023-84 NLP2023-136 pp.66-69 |
| 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 |
| R | 2024-02-29 17:10 |
Shimane | Comparison of OSS Reliability Assessment Methods Based on Deep Learning Considering the Wiener and Jump Diffusion Processes Yoshinobu Tamura, Shoichiro Miyamoto, Lei Zhou (Yamaguchi Univ.), Shigeru Yamada (Tottori Univ.) R2023-63 |
In many research fields, the methods based on deep learning have been proposed. In this paper, we propose the method of ... [more] | R2023-63 pp.46-51 |
|
| SIP, SP, EA, IPSJ-SLP [detail] | 2024-02-29 15:45 |
Okinawa | (Primary: On-site, Secondary: Online) |
We have developed automatic speech recognition and dialect identification techniques by using COJADS, a corpus of Japane... [more] | ||
| KBSE | 2024-01-24 09:10 |
Kagoshima | (Primary: On-site, Secondary: Online) |
Datetime Feature Recommendation System by Using Data Column Names Satoshi Masuda, Tomohiro Takeda (TCU) KBSE2023-58 |
Analysis to gain new knowledge from huge amounts of data is called data science, and its widespread use is now socially ... [more] | KBSE2023-58 pp.43-48 |
| SS, MSS | 2024-01-18 15:05 |
Ishikawa | (Primary: On-site, Secondary: Online) |
Development of Management Methods against Inappropriate Data Segments in Bus Passenger OD Estimation using Person Tracking Methods Tsubasa Nishiura, Soichiro Yokoyama, Tomohisa Yamashita, Hidenori Kawamura (Hokkaido Univ.) MSS2023-69 SS2023-48 |
We are advancing the development of a passenger Origin-Destination (OD) estimation system using bus passengerboarding an... [more] | MSS2023-69 SS2023-48 pp.99-104 |
| NS, RCS (Joint) |
2023-12-15 13:25 |
Fukuoka | Kyushu Institute of Technology Tobata campus, and Online (Primary: On-site, Secondary: Online) |
[Invited Talk]
Research Topics in Programmable Data Planes Junji Takemasa, Yuki Koizumi, Toru Hasegawa (Osaka Univ.) NS2023-146 RCS2023-200 |
The processing speed of the CPU, which has been a promising platform for packet processing, cannot keep up with the incr... [more] | NS2023-146 RCS2023-200 p.119(NS), p.122(RCS) |
| SANE | 2023-12-07 15:30 |
Overseas | Surakarta, Indonesia (Primary: On-site, Secondary: Online) |
Automated Preprocessing System for Landsat Data to Produce Level 0 Reformatted Product (L0Rp) Dinari Nikken Sulastrie Sirin, Panji Rachman Ramadan, Suhermanto, Hidayat Gunawan, Bayu Satya Adhitama, Ali Syahputra Nasution (BRIN) SANE2023-63 |
The launch of the Landsat-9 satellite on September 27, 2021, followed by the reception of Landsat-9 data in the third qu... [more] | SANE2023-63 pp.23-27 |
| ICM, NS, CQ, NV (Joint) |
2023-11-22 09:00 |
Ehime | Ehime Prefecture Gender Equality Center (Primary: On-site, Secondary: Online) |
Evaluation of Improvement Plans to Increase the Efficiency of Performance Data Transfer for Server Systems Chika Iiyama (Ocha Univ.), Akira Hirai, Mari Yamaoka, Naoto Fukumoto (Fujitsu), Masato Oguchi (Ocha Univ.) NS2023-117 |
In recent years, demand for shared use of multiple servers has been increasing. In order to perform load balancing on th... [more] | NS2023-117 pp.38-43 |
| ICSS | 2023-11-16 13:25 |
Ishikawa | IT Business Plaza Musashi and Online (Primary: On-site, Secondary: Online) |
Real time detection for replay-attack communication in control system Koushi Nishi, Yuichi Futa (TUT), Hiroyuki Okazaki (Shinshu University) ICSS2023-52 |
Attacks on control system in factory and power plant are increasing every year. Therefore, System that monitor communica... [more] | ICSS2023-52 pp.7-14 |
| RISING (3rd) |
2023-10-31 14:00 |
Hokkaido | Kaderu 2・7 (Sapporo) | [Poster Presentation]
Optimal Compression Rate for Multiple Data Compression Techniques in Data Parallel Distributed Deep Learning Ryudai Fukuda, Takuji Tachibana (Univ. Fukui) |
In distributed deep learning, where multiple processors are used, the learning time can be significantly reduced by exec... [more] | |
| OCS, LQE, OPE | 2023-10-19 10:30 |
Kochi | (Primary: On-site, Secondary: Online) |
Study on Optical Aggregation of SP-PAM4 Signals into DP-QPSK Signal Using PM-HNLF Yuto Fujihara, Daisuke Hisano, Akihiro Maruta, Ken Mishina (Osaka Univ.) OCS2023-26 OPE2023-81 LQE2023-28 |
All-optical modulation format conversions and signal aggregation/de-aggregations have been proposed as techniques to con... [more] | OCS2023-26 OPE2023-81 LQE2023-28 pp.1-6 |
| MIKA (3rd) |
2023-10-10 15:35 |
Okinawa | Okinawa Jichikaikan (Primary: On-site, Secondary: Online) |
[Poster Presentation]
A Consideration of Data Smoothing and Weight Orthogonalization in Blind Signal Separation Using Kurtosis Maximization Algorithm Shogo Osakabe, Nobuyoshi Kikuma, Kunio Sakakibara, Yoshiki Sugimoto (NITech) |
With the recent rapid evolution in wireless communications, the demand for high-quality, low-latency transmission and th... [more] | |
| NS | 2023-10-05 10:10 |
Hokkaido | Hokkaidou University + Online (Primary: On-site, Secondary: Online) |
[Encouragement Talk]
Communication Scheduling Based on Heuristic Algorithm in Distributed Deep Learning Ryudai Fukuda, Takuji Tachibana (Univ. Fukui) NS2023-86 |
In distributed deep learning, where multiple processors are used, the learning time can be significantly reduced by exec... [more] | NS2023-86 pp.83-88 |
| NLC | 2023-09-06 13:45 |
Osaka | Osaka Metropolitan University. Nakamozu Campus. (Primary: On-site, Secondary: Online) |
An Investigation of the Performance of Large-scale Generative Language Models on Subjective and Objective Emotion Estimation Mizuki Tada, Makoto Okada, Naoki Mori (Osaka Metropolitan Univ.) NLC2023-2 |
The cost of annotating datasets is often an issue in natural language processing tasks. One way to reduce costs is to us... [more] | NLC2023-2 pp.7-11 |
| R | 2023-07-28 15:30 |
Hokkaido | (Primary: On-site, Secondary: Online) |
Deep Learning Approach for OSS Reliability Assessment Based on Data Preprocessing Considering the Wiener Process Yoshinobu Tamura (Yamaguchi Univ.), Shigeru Yamada (Tottori Univ.) R2023-16 |
In many open source software, the development style based on the database of general bug tracking systems is the normal ... [more] | R2023-16 pp.33-38 |
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