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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CQ, CS (Joint) |
2024-05-16 17:00 |
Aichi | (Primary: On-site, Secondary: Online) |
[Special Invited Talk]
Reconstruction of Campus Network Based on Quality of Experience (QoE) Kyoko Yamori (Asahi Univ.) |
(To be available after the conference date) [more] | |
| HIP, HCS, HI-SIGCOASTER [detail] | 2024-05-13 13:20 |
Okinawa | Okinawa Industry Support Center | Strategies to encode non-speech sounds into language: A developmental study Kaede Hattori, Shoko Miyauchi, Kazuhide Hashiya (Kyushu Univ.) |
[more] | |
| ICM | 2024-03-21 09:20 |
Okinawa | Okinawa Prefectural Museum and Art Museum (Primary: On-site, Secondary: Online) |
Intuitive Interaction System Based on Leg Movement Recognition Using Chair-embedded Camera Kaito Hamagaki, Shingo Ata, Manato Fujimoto (Osaka Metropolitan Univ.)  ICM2023-45 |
Virtual Reality (VR) technology has rapidly evolved, expanding into education, healthcare, and entertainment, offering u... [more] | ICM2023-45 pp.1-6 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-13 13:20 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
[Invited Talk]
The Past, Current and Future of Fashion Image Retrieval: Toward a User-Centered Orientation Ling Xiao (UTokyo) IMQ2023-28 IE2023-83 MVE2023-57 |
Fashion image retrieval (FIR) plays a pivotal role in enhancing the online shopping experience on retail and e-commerce ... [more] | IMQ2023-28 IE2023-83 MVE2023-57 pp.87-89 |
| IE, MVE, CQ, IMQ (Joint) [detail] |
2024-03-14 15:20 |
Okinawa | Okinawa Sangyo Shien Center (Primary: On-site, Secondary: Online) |
Efficient regularizer for 4D light field image denoising based on graph-learning Rino Yoshida (TUS), Kazuya Kodama (NII), Gene Cheung (York Univ.), Takayuki Hamamoto (TUS) IMQ2023-56 IE2023-111 MVE2023-85 |
Advanced 3D visual media as promising technology often require 4D light fields composed of dense multi-view images for a... [more] | IMQ2023-56 IE2023-111 MVE2023-85 pp.235-240 |
| ET | 2024-03-03 10:00 |
Miyazaki | Miyazaki University | Alleviating Persistence in Learning Strategies with a Model of Empathy for Others' Learning Experience
-- Designing Interaction Scenario with a Social Robot -- So Sasaki, Akihiro Kashihara (UEC) ET2023-64 |
Effective learning requires learners to properly use learning strategies according to learning phases. However, it is no... [more] | ET2023-64 pp.69-76 |
| PRMU, MVE, VRSJ-SIG-MR, IPSJ-CVIM | 2024-01-26 15:34 |
Kanagawa | Keio Univ. (Hiyoshi Campus) | Comparison of Imbalanced Data Handling Techniques in Emotion Estimation of Expressway Service Area Workers using Stacking Ensemble Learners for Complex Decision Boundaries Akihiro Sato, Satoki Ogiso, Ryosuke Ichikari, Takeshi Kurata (AIST) PRMU2023-47 |
Estimating emotions of workers is promising to promote health and productivity management, while it has difficulty in c... [more] | PRMU2023-47 pp.40-45 |
| ICM, NS, CQ, NV (Joint) |
2023-11-22 09:25 |
Ehime | Ehime Prefecture Gender Equality Center (Primary: On-site, Secondary: Online) |
A Study on Transfer of Decision Tree for Operation of Future Managed Networks Takaaki Moriya, Takashi Mukai, Manabu Nishio, Ai Tsunoda, Ken Kanishima (NTT) ICM2023-26 |
When we build a new managed network, we need knowledge to solve various failures that will be occurred in the network. H... [more] | ICM2023-26 pp.20-25 |
| KBSE, SC | 2023-11-18 15:10 |
Miyagi | Sento Kaikan | Research to improve the accuracy of inferring program defects using deep learning Kazuhiko Ogawa, Takako Nakatani (OUJ) KBSE2023-50 SC2023-33 |
Experienced developers seem to be able to identify defects in programs created by beginners at a glance. We applied sup... [more] |
KBSE2023-50 SC2023-33 pp.93-98 |
| ET | 2023-11-11 15:55 |
Kagawa | Kagawa University Saiwai-cho (Main) Campus / Online (Primary: On-site, Secondary: Online) |
Proposal for a Food Cutting Training System Using Haptic Devices and CT Data Yukitoshi Nakazato, Toru Kano (Ibaraki Univ.) ET2023-33 |
Food loss is one of the contemporary social problems in Japan. To address wastage from excessive removal or cooking mist... [more] | ET2023-33 pp.51-55 |
| MIKA (3rd) |
2023-10-10 15:35 |
Okinawa | Okinawa Jichikaikan (Primary: On-site, Secondary: Online) |
[Poster Presentation]
A Study on CNN based Cucumber Classification System Hotaka Hoshino, Takuya Shindo, Takefumi Hiraguri, Nobuhiko Itoh (NIT) |
Cucumber farmers classify the harvested cucumbers based on specific conditions and get the classified cucumbers on the m... [more] | |
| ICM | 2023-07-13 16:40 |
Hokkaido | Sun Reflation Hakodate (Primary: On-site, Secondary: Online) |
[Invited Talk]
Application-aware RAN control technology to support DX promotion using 5G and IoT Eiji Takahashi, Takeo Onishi (NEC) ICM2023-18 |
It has become increasingly important for industries to promote digital transformation by utilizing 5G, Internet of Thing... [more] | ICM2023-18 pp.38-39 |
| SeMI, RCS, RCC, NS, SR (Joint) |
2023-07-13 16:25 |
Osaka | Osaka University Nakanoshima Center + Online (Primary: On-site, Secondary: Online) |
[Short Paper]
A study of Cross-Layer Adaptation using Learning in Wireless MAC Protocols Koshiro Aruga, Takeo Fujii (UEC) SR2023-40 |
In recent years, with the development of wireless communication technology, networks have become larger and more complex... [more] | SR2023-40 pp.55-57 |
| IMQ, IE, MVE, CQ (Joint) [detail] |
2023-03-16 16:05 |
Okinawa | Okinawaken Seinenkaikan (Naha-shi) (Primary: On-site, Secondary: Online) |
Automated Driving Methods Using Federated Learning Koki Ono, Celimuge Wu, Tsutomu Yoshinaga (UEC) CQ2022-99 |
When learning autonomous driving behavior using machine learning, a huge amount of driving data is required, and a large... [more] | CQ2022-99 pp.96-101 |
| NC, MBE (Joint) |
2023-03-14 15:50 |
Tokyo | The Univ. of Electro-Communications (Primary: On-site, Secondary: Online) |
Curiosity-based deep reinforcement learning with profit sharing Kouki Hayashi, Kazuma Yamaguchi, Yukari Yamauchi (Nihon Univ.) NC2022-107 |
Recently, "DQN with PS," which incorporates profit sharing in deep reinforcement learning, was proposed. This method sp... [more] | NC2022-107 pp.90-93 |
| TL | 2023-03-11 14:15 |
Online | Online | Emergent Inference in Grammatical Machineries
-- Acquisition of Associative Knowledge into Deductive Systems -- Yasunari Harada (Waseda Univ.) TL2022-39 |
The essence of linguistic communication lies in "exchange of meanings" and "meaningful exchanges of messages." In recent... [more] | TL2022-39 pp.30-35 |
| CQ, CBE (Joint) |
2023-01-26 10:35 |
Ibaraki | Epochal Tsukuba International Congress Center (Primary: On-site, Secondary: Online) |
Verification of sensory change in AR space by bounce estimation using DeepLearning Masaya Matsukawa, Koji Yamada (Ryukyu Univ) CQ2022-62 |
Research has been conducted to realize interaction between virtual objects and real space by recognizing objects and spa... [more] | CQ2022-62 pp.6-10 |
| MSS, SS | 2023-01-11 10:50 |
Osaka | (Primary: On-site, Secondary: Online) |
Comparison of Machine Learning Methods for Decision of Acupoints in Acupuncture and Moxibustion Treatment Hang Yang (Yamaguchi Univ.), Ren Wu (Yamaguchi Junior College), Mitsuru Nakata, Qi-Wei Ge (Yamaguchi Univ.) MSS2022-54 SS2022-39 |
After thousands of years of development, a large number of clinical experiences of acupuncture and moxibustion treatment... [more] | MSS2022-54 SS2022-39 pp.54-59 |
| IBISML | 2022-12-22 10:10 |
Kyoto | Kyoto University (Primary: On-site, Secondary: Online) |
IBISML2022-40 |
Supervised learning, the core technology for current "AI", predicts the future as an extension of the experienced past a... [more] | IBISML2022-40 p.1 |
| DC | 2022-12-16 15:00 |
Yamaguchi | (Primary: On-site, Secondary: Online) |
Learning of train control measures by means of Deep Q-Network
-- Preliminary study with a single train control -- Shogo Igarashi, Takumi Fukuda, Sei Takahashi, Hideo Nakamura (Nihon Univ), Tetsuya Takata (Kyosan Electric Manufacturing) DC2022-77 |
Although the predictive fuzzy control technique has been put to practical use as a train control strategy for automatic ... [more] | DC2022-77 pp.26-29 |
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