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All Technical Committee Conferences (All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| CQ, IMQ, MVE, IE (Joint) [detail] |
2022-03-09 15:55 |
Online | Online (Zoom) | Model selection for link quality prediction based on physical space information Hisashi Nagata, Riichi Kudo, Kahoko Takahashi, Tomoaki Ogawa (NTT)  CQ2021-106 |
With the development of wireless communication technology, it is expected that all things will be connected to the netwo... [more] | CQ2021-106 pp.31-36 |
| RCS, SIP, IT | 2022-01-20 15:10 |
Online | Online | [Invited Talk]
Wireless link quality prediction using physical space information in Society 5.0 Riichi Kudo, Kahoko Takahashi, Hisashi Nagata, Tomoki Murakami, Tomoaki Ogawa (NTT) IT2021-44 SIP2021-52 RCS2021-212 |
Thanks to the great advances in wireless communication systems, many types of the wireless terminals are available. It i... [more] | IT2021-44 SIP2021-52 RCS2021-212 pp.93-94 |
| CQ, MIKA (Joint) |
2021-09-09 14:05 |
Online | Online | [Invited Talk]
Deep Learning based position estimation method using WLAN CSI feedback Riichi Kudo, Kahoko Takahashi, Tomoki Murakami, Tomoaki Ogawa (NTT) CQ2021-45 |
Thanks to the great advances in wireless communication systems, many types of the wireless terminals are available. It i... [more] | CQ2021-45 pp.40-45 |
| CQ, MIKA (Joint) |
2021-09-10 10:40 |
Online | Online | Link Quality Prediction using Multiple cameras in Indoor Environment for Wireless LAN Systems Kahoko Takahashi, Riichi Kudo, Tomoaki Ogawa (NTT) CQ2021-53 |
This paper proposes a received power prediction scheme that uses deep-neural-network based camera image object detection... [more] | CQ2021-53 pp.77-81 |
| SIP, IT, RCS | 2021-01-22 12:30 |
Online | Online | Deep Learning based Link Quality Prediction for Autonomous Mobility Robots Riichi Kudo, Kahoko Takahashi, Tomoki Murakami, Tomoaki Ogawa (NTT) IT2020-102 SIP2020-80 RCS2020-193 |
Highly advanced mobility robots are expected to be managed, monitored, or efficiently controlled by using wireless commu... [more] | IT2020-102 SIP2020-80 RCS2020-193 pp.218-223 |
| MIKA (3rd) |
2020-10-09 11:05 |
Niigata | (Primary: On-site, Secondary: Online) |
Wireless link quality prediction using camera/sensor images based on machine learning Riichi Kudo, Kahoko Takahashi, Tomoaki Ogawa (NTT) |
[more] | |
| SR, NS, SeMI, RCC, RCS (Joint) |
2020-07-10 10:20 |
Online | Online | Performance evaluation of SHF throughput prediction based on deep neural network detector Riichi Kudo, Kahoko Takahashi, Takeru Inoue, Kohei Mizuno (NTT) SeMI2020-12 |
(To be available after the conference date) [more] | SeMI2020-12 pp.51-56 |
| SeMI | 2020-01-30 15:50 |
Kagawa | Locomotion robot based wireless LAN link quality prediction using machine learning Riichi Kudo, Matthew Cochrane, Kahoko Takahashi, Takeru Inoue, Kohei Mizuno (NTT) SeMI2019-103 |
[more] | SeMI2019-103 pp.23-28 |
|
| RISING (2nd) |
2019-11-26 10:30 |
Tokyo | Fukutake Learning Theater, Hongo Campus, Univ. Tokyo | [Poster Presentation]
[MIKA/RISING Collaboration] Wireless link quality prediction based on environment recognition with smart connected devices Riichi Kudo, Kahoko Takahashi, Takeru Inoue, Kohei Mizuno (NTT) |
[more] | |
| MIKA (2nd) |
2019-10-03 11:15 |
Hokkaido | Hokkaido Univ. | [Poster Presentation]
Vision information based wireless link quality prediction Kahoko Takahashi, Riichi Kudo, Takeru Inoue, Kohei Mizuno (NTT) |
The advancement of wireless communication technologies is accelerating the widespread use of the various connected devic... [more] | |
| MIKA (2nd) |
2019-10-04 10:15 |
Hokkaido | Hokkaido Univ. | [Poster Presentation]
Locomotion robot based wireless link quality prediction Riichi Kudo, Kahoko Takahashi, Takeru Inoue, Kohei Mizuno (NTT) |
[more] | |
| CQ | 2019-08-27 16:15 |
Hokkaido | Hakodate arena | [Invited Talk]
Potentiality of machine learning based next generation wireless communication systems for smart connected devices Riichi Kudo, Kahoko Takahashi, Takeru Inoue, Kohei Mizuno (NTT) CQ2019-72 |
The connected devices which are autonomously operated need to recognize its position and surrounding environment by usin... [more] | CQ2019-72 pp.79-84 |
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