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All Technical Committee Conferences (Searched in: Recent 10 Years)
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Search Results: Conference Papers |
Conference Papers (Available on Advance Programs) (Sort by: Date Descending) |
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Committee |
Date Time |
Place |
Paper Title / Authors |
Abstract |
Paper # |
SIS, IPSJ-AVM |
2022-06-10 11:40 |
Fukuoka |
KIT(Wakamatsu Campus) (Fukuoka, Online) (Primary: On-site, Secondary: Online) |
An embedded-oriented sound classification system using reservoir computing Yuichiro Tanaka, Issei Uchino (Kyutech), Kazunobu Ohkuri (Sony), Hakaru Tamukoh (Kyutech) SIS2022-9 |
Although deep neural networks (DNNs) have achieved state-of-the-art results in sound classification tasks in recent year... [more] |
SIS2022-9 pp.41-44 |
UWT (2nd) |
2022-03-01 14:05 |
Online |
Online (Online) |
Formulation and Validation of the Transmission Factor Between Two Electrically Small Dipole Antennas Immersed in Seawater Takashi Kawamura, Takuma Matsushita, Toshinori Kondo, Futoshi Takeuchi, Kazuhiro Hongo, Yasuhiro Matsui, Takashi Takinami, Akihiro Horii, Kazunobu Ohkuri (Sony Group) |
As one of the theoretical approaches to reveal antenna behavior in the sea, it has been reported that the impedances of ... [more] |
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WPT, UWT (Joint) |
2021-11-12 14:45 |
Online |
Online (Online) |
Formulation, Validation, and Extensibility Study on the Impedance of Underwater Dipole Antennas Takuma Matsushita, Takashi Kawamura, Toshinori Kondo, Futoshi Takeuchi, Yasuhiro Matsui, Takashi Takinami, Kazuhiro Hongo, Akihiro Horii, Kazunobu Ohkuri (Sony Group Corp.) |
This paper describes the theoretical formulation for half sheath dipole antenna(HSDA) and adaption area of this formulat... [more] |
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SDM, ICD, ITE-IST [detail] |
2021-08-18 09:30 |
Online |
Online (Online) |
[Invited Talk]
Analog in-memory computing in FeFET based 1T1R array for low-power edge AI applications Daisuke Saito, Toshiyuki Kobayashi, Hiroki Koga (SONY), Yusuke Shuto, Jun Okuno, Kenta Konishi (SSS), Masanori Tsukamoto, Kazunobu Ohkuri (SONY), Taku Umebayashi (SSS), Takayuki Ezaki (SONY) SDM2021-36 ICD2021-7 |
Deep neural network (DNN) inference for edge AI requires low-power operation, which can be achieved by implementing mass... [more] |
SDM2021-36 ICD2021-7 pp.33-37 |
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