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 Conference Papers (Available on Advance Programs)  (Sort by: Date Descending)
 Results 1 - 6 of 6  /   
Committee Date Time Place Paper Title / Authors Abstract Paper #
SeMI, IPSJ-UBI, IPSJ-MBL 2024-03-01
11:50
Fukuoka   Proposal of a method for analyzing the flow of people near stations based on multiple data integration
Yasuhiro Aoki, Yoshiki Mashima, Yoshihiko Suzuki (Toshiba Infrastructure S&S co,ltd) SeMI2023-84
With the spread of smartphones, it has become possible to know people's movement history in detail, and people flow pred... [more] SeMI2023-84
pp.76-81
MSS, SS 2023-01-10
16:00
Osaka
(Primary: On-site, Secondary: Online)
Optimal operation planning of energy system for large-scale hydrogen plant -- A Study of Demand Response Optimization --
Takashi Akiba (ToshibaESS), Shingo Tamaru (TISS), Fumiyuki Yamane (ToshibaESS) MSS2022-49 SS2022-34
Regarding the operation planning function in the hydrogen energy operation system that manages the entire FH2R facility ... [more] MSS2022-49 SS2022-34
pp.25-30
SANE 2018-11-08
14:10
Overseas China (Xuchang) Imaging Performance of Millimeter Wave SAR for Portable Weapon Detection
Koki Homma, Hiroyoshi Yamada, Ryoichi Sato, Yoshio Yamaguchi (Niigata Univ.), Hiroki Mori (Toshiba), Kazuyoshi Takagi, Hironori Dobashi, Yasushi Murakami (Toshiba Infrastructure Systems & Solutions) SANE2018-58
Concealed weapon detection by electromagnetic wave have been attracting attention recently. Currently, several products ... [more] SANE2018-58
pp.17-20
PRMU, CNR 2018-02-20
13:20
Wakayama   [Special Talk]
Hironobu Fujiyoshi (Chubu Univ.), Kei Okada (Univ. of Tokyo), Koji Ehara (Toshiba Infrastructure Systems & Solutions), Gustavo Garcia (NAIST) PRMU2017-170 CNR2017-48
 [more] PRMU2017-170 CNR2017-48
pp.145-154
SANE 2018-01-25
14:50
Nagasaki Nagasaki Prefectural Art Museum Deep Learning for End-to-End Automatic Target Recognition from Synthetic Aperture Radar Imagery
Hidetoshi Furukawa (Toshiba Infrastructure Systems & Solutions) SANE2017-92
The standard architecture of synthetic aperture radar (SAR) automatic target recognition (ATR) consists of three stages:... [more] SANE2017-92
pp.35-40
SANE 2017-08-24
13:50
Osaka OIT UMEDA Campus Deep Learning for Target Classification from SAR Imagery -- Data Augmentation and Translation Invariance --
Hidetoshi Furukawa (Toshiba Infrastructure Systems & Solutions) SANE2017-30
This report deals with translation invariance of convolutional neural networks (CNNs) for automatic target recognition (... [more] SANE2017-30
pp.13-17
 Results 1 - 6 of 6  /   
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