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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| RCS | 2024-06-19 11:40 |
Okinawa | (Primary: On-site, Secondary: Online) |
A Double Deep Q Network Based Fully Autonomous Distributed Transmission Parameter Selection Method for Mobile IoT Applications Seiya Sugiyama (UEC), Keigo Makizoe, Maki Arai, Mikio Hasegawa (TUS), Ohtsuki Tomoaki (Keio Univ.), Li Aohan (UEC) |
(To be available after the conference date) [more] | |
| RCS | 2024-06-19 11:50 |
Okinawa | (Primary: On-site, Secondary: Online) |
Environment-Specific Beam Search Using Machine Learning for Connected Autonomous Vehicle Ryo Iwaki, Jin Nakazato (UT), Kazuki Maruta (TUS), Manabu Tsukada, Hideya Ochiai, Hiroshi Esaki (UT) |
(To be available after the conference date) [more] | |
| 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 |
| AI | 2023-09-12 15:15 |
Hokkaido | A Study on the Implementation of Cooperative CAVs by Sharing the Observation Information Using Simulations and Considerations Based on Qualitative Evaluation Ken Matsuda (Graduate School of FUN), Ei-Ichi Osawa (FUN) AI2023-4 |
This study focuses on cooperative connected autonomous vehicles (cooperative CAVs). This research aims to propose a simu... [more] | AI2023-4 pp.19-24 |
|
| CCS, NLP | 2023-06-09 11:10 |
Tokyo | Tokyo City Univ. | A study on learning Koopman operators from synchrophasor data on distribution voltage amplitudes Tadahiro Yano, Yoshihiko Susuki (Kyoto Univ.) NLP2023-21 CCS2023-9 |
In recent years, the so-called micro-Phasor Measurement Unit ($mu$PMU) has become a promising new option for managing AC... [more] | NLP2023-21 CCS2023-9 pp.35-38 |
| SR | 2023-05-12 13:05 |
Hokkaido | Center of lifelong learning Kiran (Higashi Muroran) (Primary: On-site, Secondary: Online) |
[Invited Talk]
Wireless Ad Hoc Federated Learning
-- Toward A Fully Autonomous and Decentralized Federated Learning -- Hideya Ochiai (UT) SR2023-19 |
Wireless Ad Hoc Federated Learning (WAFL) fully decentralizes Federated Learning (FL) which is implemented on a client-s... [more] | SR2023-19 p.90 |
| 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 |
| 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 |
| PRMU, IBISML, IPSJ-CVIM [detail] | 2023-03-03 09:20 |
Hokkaido | Future University Hakodate (Primary: On-site, Secondary: Online) |
3D Point Cloud based Object Recognition and Auto True-Value System Construction for Autonomous Driving Bin Zhang, Congzhi Ren, Hun-ok Lim (KU) PRMU2022-100 IBISML2022-107 |
In this paper, an object recognition system based on 3D point cloud information is proposed and an automatic true value ... [more] | PRMU2022-100 IBISML2022-107 pp.217-219 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2023-02-22 14:00 |
Hokkaido | Hokkaido Univ. | Hierarchical Minimum-Sized Object Detection Method using Clustering Algorithm for UAV Autonomous Flight Yusei Horikawa, Makoto Sugaya, Tetsuya Matsumura (Nihon Univ) |
This paper describes an efficient minimum-sized object detection method in high-Resolution images for UAV autonomous fli... [more] | |
| RCS, NS (Joint) |
2022-12-16 13:35 |
Aichi | Nagoya Institute of Technology, and Online (Primary: On-site, Secondary: Online) |
[Invited Talk]
Wireless Ad Hoc Federated Learning
-- A Fully Distributed Cooperative Machine Learning -- Hideya Ochiai (UT) NS2022-145 RCS2022-203 |
Federated Learning (FL) is a feature topic in the era of privacy awareness that allows machine learning without collecti... [more] | NS2022-145 RCS2022-203 p.83(NS), p.94(RCS) |
| TL | 2022-12-11 11:30 |
Online | Online | Negotiations with Semiotic Environments and Autonomous Learning of Foreign Languages
-- How to Make Sense out of Linguistic and Acoustic Landscapes -- Yasunari Harada (Waseda Univ.), Miwa Morishita (Kobe Gakuin Univ.) TL2022-28 |
The essence of linguistic communication lies in “exchange of meanings” and “meaningful exchanges of messages.” In learni... [more] | TL2022-28 pp.10-15 |
| RISING (3rd) |
2022-10-31 15:00 |
Kyoto | Kyoto Terrsa (Day 1), and Online (Day 2, 3) | [Poster Presentation]
Detecting Object through Federated Learning with an autonomous driving simulator Generated Data Atsushi Nakajima, Satoshi Ohzahata, Ryo Yamoto (UEC) |
The amount of data generated by automobiles is enormous and will be processed using machine learning. In conventional ma... [more] | |
| ICM, IPSJ-CSEC, IPSJ-IOT | 2022-05-20 14:15 |
Nagano | (Primary: On-site, Secondary: Online) |
Anomaly Event Classification Method using Observability Data in Autonomous Control Loop Yukitsugu Sasaki, Masaru Sakai, Kensuke Takahashi, Satoshi Kondou (NTT) ICM2022-9 |
An autonomous control loop system has been proposed in which each operation part operates autonomously by making the fun... [more] | ICM2022-9 pp.42-46 |
| CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-11 14:15 |
Online | Online (Zoom) | Research on state recognition and behavior prediction of surrounding people using a stereo camera in a human coexistence type autonomous mobile robotResearch on State Recognition and Behavior Prediction of Surrounding People using a Stereo Camera in a Huma Masaaki Hayashi, Jun Ohya (Waseda Univ), Junji Yamato (KUTE-TOKYO), Mitsuhiro Kamezaki (Waseda Univ/JST PRESTO), Kyousuke Saitou, Tarou Hamada, Eriko Sakurai, Shigeki Sugano (Waseda Univ) IMQ2021-52 IE2021-114 MVE2021-81 |
In recent years, major advanced countries have been developing autonomous mobile robots to replace human labor as a coun... [more] | IMQ2021-52 IE2021-114 MVE2021-81 pp.216-221 |
| CAS, CS | 2022-03-04 15:55 |
Online | Online | Federated Learning with Correlated Sensing Data in Wireless Networks Keita Hibari, Masaya Kambara, Tomotaka Kimura, Jun Cheng (Doshisha Univ) CAS2021-99 CS2021-101 |
Federated leaning in wireless networks is considered where devices are gathered in several locations and the sensing dat... [more] | CAS2021-99 CS2021-101 pp.136-140 |
| PN | 2021-08-30 14:00 |
Online | Online | [Invited Lecture]
Optical Link Diagnosis Technology that Applies Deep Learning to DSP Data and its Implementation on an Open Platform Takafumi Tanaka, Tetsuro Inui, Shingo Kawai (NTT) PN2021-16 |
In order to reduce the operational expenditure (OPEX) of optical networks, researches on autonomous optical network oper... [more] | PN2021-16 p.28 |
| TL | 2021-07-03 16:20 |
Online | Online | Significance of Classroom "Noises" in Autonomous Mutual Learning Yasunari Harada, Akatsuka Yuya (Waseda U.), Lisa Nabei (Tokai U.), Yasushi Tsubota (KITech), Miwa Morishita (Kobe Gakuin University) TL2021-5 |
The authors have collected audio and video recordings of students interacting among themselves in tasks intended to help... [more] | TL2021-5 pp.15-19 |
| CPSY, RECONF, VLD, IPSJ-ARC, IPSJ-SLDM [detail] | 2021-01-26 09:50 |
Online | Online | FPGA Implementation of Semantic Segmentation on LWIR Images for Autonomous Robot Yuichiro Niwa (ATLA), Taiki Fujii (eSOL) VLD2020-57 CPSY2020-40 RECONF2020-76 |
Recently, deep learning of images has made remarkable progress, and its results are being applied to the automatic reco... [more] |
VLD2020-57 CPSY2020-40 RECONF2020-76 pp.101-106 |
| KBSE | 2021-01-23 13:05 |
Online | Online | DevOps Assurance Cases for Autonomous Vehicles Systems Yudai Koike (Nihon Univ.), Manabu Okada (Tier4), Toshinori Takai (Change Vision), Takumi Okuma, Yutaka Matsuno (Nihon Univ.) KBSE2020-29 |
With the advancement of deep learning technologies, autonomous vehicle systems will be realized. However, due to the ind... [more] | KBSE2020-29 pp.1-6 |
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