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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NLP, MSS | 2024-03-13 15:25 |
Misc. | Kikai-Shinko-Kaikan Bldg. | Machine learning-based solubility prediction and meta-heuristic search for multiple mutation patterns Kaisei Kojima, Kazutoshi Sakakibara, Masaki Nakamura (Toyama Prefectural Univ.), Daisuke Matsui (Ritsumeikan Univ.)  MSS2023-80 NLP2023-132 |
In order to solubilize insoluble proteins that cannot be used for industrial purposes, experiments have been performed t... [more] | MSS2023-80 NLP2023-132 pp.48-53 |
| SS | 2024-03-09 09:30 |
Okinawa | (Primary: On-site, Secondary: Online) |
Investigating indicators of distortion in CNN models using statistical metamorphic testing Tsuchiya Takumi, Okano Kozo, Ogata Shinpei (Shinshu Univ), Nakajima Shin (NII) SS2023-77 |
In quality evalution of machine learning systems, it is important to determine whether the learning parameter (weight) v... [more] | SS2023-77 pp.168-173 |
| MI | 2024-03-04 09:00 |
Okinawa | OKINAWAKEN SEINENKAIKAN (Primary: On-site, Secondary: Online) |
Distance-informed adversarial learning for metal artifact reduction Daisuke Shigemori, Megumi Nakao (Kyoto Univ.) MI2023-62 |
In this study, we propose an adversarial learning framework that utilises distance information from metal to reduce CT m... [more] | MI2023-62 pp.95-98 |
| ET | 2023-12-16 12:50 |
Okayama | Tsushima Campus,Okayama University | The Effects of Reviewing with Digital Drills Using One Student One Device in Arithmetic Class on Students' Motivation to Learn
-- Effectiveness of Visualization and Sharing of Digital Drill Progress -- Wataru Igawa, Hikaru Agatsuma, Takeaki Shionome (Teikyo Univ.) ET2023-38 |
With the GIGA School Program from 2019, each elementary school has been equipped with one student one device, and a high... [more] | ET2023-38 pp.13-18 |
| IA | 2023-09-21 17:55 |
Hokkaido | Hokkaido Univeristy (Primary: On-site, Secondary: Online) |
Development and Evaluation of Construction Method of Machine Learning Model for Automated Design of Automotive Ethernet Yasuhiro Mori, Hiroshi Yamamoto (Ritsumeikan Univ.), Yojiro Suyama, Tatsuya Izumi (Sumitomo Electric Industries, Ltd.), Hirofumi Urayama (AutoNetwork Technologies, Ltd.), Shiho Kobayashi, Hideaki Tani (Sumitomo Electric System Solutions, Ltd) IA2023-20 |
In recent years, Ethernet is attracting attention as a technology for constructing in-vehicle networks. As a result, the... [more] | IA2023-20 pp.54-59 |
| ET | 2023-05-13 13:35 |
Online | Online | Can Metaverse Create Effective and Effectual Education/Learning Environment? Toyohide Watanabe (NISRI) ET2023-2 |
The objective in Metaverse is to construct another activity space virtually, different from our real space, and also mak... [more] | ET2023-2 pp.8-13 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-02 11:05 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
A Study of Word Lip-Reading using Meta Learning Michinari Kodama, Takeshi Saitoh (kyutech) PRMU2022-77 IBISML2022-84 |
Lip-reading technology, which estimates utterance content using only visual information, is a kind of supervised learnin... [more] | PRMU2022-77 IBISML2022-84 pp.102-106 |
| CAS, CS | 2023-03-01 11:45 |
Fukuoka | Kitakyushu International Conference Center (Primary: On-site, Secondary: Online) |
Demodulation from Meta-Learning with Few Pilot Symbols in Massive Sensor Networks Kuniyasu Yamamoto, Tomotaka Kimura, Jun Chen (Doshisha Univ.) CAS2022-101 CS2022-78 |
Demodulation from meta-learning with few pilot symbols in massive sensor networks is proposed. In the massive sensor net... [more] | CAS2022-101 CS2022-78 pp.29-34 |
| IT | 2022-07-22 15:05 |
Okayama | Okayama University of Science (Primary: On-site, Secondary: Online) |
Bayes Optimal Approximation Algorithm by Boosting-like Construction of Meta-Tree Sets in Classification on Decision Tree Model Ryota Maniwa, Naoki Ichijo, Koshi Shimada, Toshiyasu Matsushima (Waseda Univ.) IT2022-28 |
Decision trees are used for classification and regression such as predicting the objective variable corresponding to the... [more] | IT2022-28 pp.67-72 |
| NS, SR, RCS, SeMI, RCC (Joint) |
2022-07-15 11:30 |
Ishikawa | The Kanazawa Theatre + Online (Primary: On-site, Secondary: Online) |
Development and Evaluation of Automated Design System of Automotive Ethernet by Linkage of Machine Learning and Meta-heuristics Yasuhiro Mori, Hiroshi Yamamoto (Ritsumeikan Univ.), Yojiro Suyama, Tatsuya Izumi (Sumitomo Electric Industries), Hirofumi Urayama (AutoNetwork Technology Research Institute), Shiho Kobayashi, Shigeki Umehara, Hideaki Tani (Sumitomo Electric System Solutions) NS2022-54 |
In recent years, Ethernet tends to be adopted as an in-vehicle network that the various computers (ECUs) are interconnec... [more] | NS2022-54 pp.131-136 |
| SIP, BioX, IE, MI, ITE-IST, ITE-ME [detail] | 2022-05-20 16:00 |
Kumamoto | Kumamoto University Kurokami Campus (Primary: On-site, Secondary: Online) |
Application of LambdaNetwork learning long-range interactions between pixels to metal artifact detection Daisuke Shigemori, Megumi Nakao, Tetsuya Matsuda (Kyoto Univ.) SIP2022-27 BioX2022-27 IE2022-27 MI2022-27 |
Although deep learning-based image transformation has been attempted to be applied to metal artifact reduction, feature ... [more] | SIP2022-27 BioX2022-27 IE2022-27 MI2022-27 pp.138-143 |
| IBISML | 2022-03-08 10:00 |
Online | Online | Estimating average causal effect of intervention in continuous variables using machine learning Yoshiaki Kitazawa (MSI) IBISML2021-30 |
The most widely discussed methods for estimating the Average Causal Effect / Average Treatment Effect are those for inte... [more] | IBISML2021-30 pp.1-7 |
| NLC | 2022-03-07 16:15 |
Online | Online | Program Information Extraction Using Gradient Boosting Hiroki Tanioka (Tokushima Univ.), Kenji Taniwaki (PLAT WORKS Corp.) NLC2021-37 |
Although video distribution services using the Internet have been launched one after another, the authors currently perf... [more] | NLC2021-37 pp.54-55 |
| MICT, EMCJ (Joint) |
2022-03-04 17:55 |
Online | Online | Design of waveguide for abdominal fat thickness estimation and investigation of measurement simulation using numerical human body model Yukiko Sawano, Takahiro Aoyagi (Tokyo Tech) EMCJ2021-80 |
This research group aims to establish a measurement method by estimating abdominal fat mass using microwaves. In previou... [more] | EMCJ2021-80 pp.37-41 |
| EA, SIP, SP, IPSJ-SLP [detail] | 2022-03-02 15:35 |
Okinawa | (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Interpolation of head-related transfer function from small amount of observation data using deep learning based on spherical wavefunction expansion Yuki Ito, Tomohiko Nakamura, Shoichi Koyama, Hiroshi Saruwatari (UTokyo) EA2021-90 SIP2021-117 SP2021-75 |
In binaural synthesis, listeners' individual head-related transfer functions (HRTFs) are necessary for highly-immersive ... [more] | EA2021-90 SIP2021-117 SP2021-75 pp.163-170 |
| MI | 2022-01-27 16:00 |
Online | Online | MI2021-86 |
The appearance of skin diseases varies greatly depending on the type, location, and severity of the disease. There have ... [more] | MI2021-86 pp.184-185 |
| HCGSYMPO (2nd) |
2021-12-15 - 2021-12-17 |
Online | Online | The Development of Online Shared Dining System
-- Designing the Online Learning Environment to Improve Collective Metacognition -- Nahoko Kusaka (DWCLA), Yuichi Nakamura (Kyoto University), Mutsuo Sano (Osaka Institute of Technology), Mutsuo Sano (KPUM), Kenji Kanbara (Kagawa University), Hideaki Hasuo (Kansai Medical University), Nobuyuki Ueda (DWCLA) |
In this research, we focus on the function of shared joint attention to improve dyadic interaction using the remote meet... [more] | |
| SRW, SeMI, CNR (Joint) |
2021-11-26 15:00 |
Tokyo | Kikai-Shinko-Kaikan Bldg. (Primary: On-site, Secondary: Online) |
[Poster Presentation]
Signal-Completion-Based Pre-Training Scheme for EEG with Various Number of Electrodes Yuma Tsurugasaki, Akihito Taya, Yoshito Tobe (Aoyama Gakuin Univ.) SRW2021-50 SeMI2021-49 CNR2021-24 |
Machine learning using electroencephalographs (EEG) data can be used to infer various human states such as emotions and ... [more] | SRW2021-50 SeMI2021-49 CNR2021-24 pp.79-81(SRW), pp.66-68(SeMI), pp.56-58(CNR) |
| R | 2021-07-17 14:25 |
Online | Virtual | Refined Ensemble Learning Algorithms for Software Bug Prediction
-- Metaheuristic Approach -- Keisuke Fukuda, Tadashi Dohi, Hiroyuki Okamura (Hiroshima Univ.) R2021-19 |
In this paper, we propose to apply three metaheuristic algorithms; latin hypercube sampling, ABC (artificial bee colon... [more] |
R2021-19 pp.18-23 |
| COMP | 2021-03-08 15:15 |
Online | Online | A hyper-heuristic for the maximum clique problem Kazuho Kanahara, Kengo Katayama (OUS), Etsuji Tomita (UEC) COMP2020-34 |
The maximum clique problem (MCP) is one of the most important combinatorial optimization problems that has many practica... [more] | COMP2020-34 pp.30-37 |
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