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Committee Date Time Place Paper Title / Authors Abstract Paper #
SR 2024-05-20
15:55		 Kagoshima Yokacenter (Kagoshima)
(Primary: On-site, Secondary: Online)		 Development of an indoor location estimation method using Wi-Fi (1) -- Optimization of access point selection methods and data set volume --
Yudai Sunagozaka, Takashi Ohkawaara, Rei Hirata, Atsushi Koizumi, Hiroshi Oguma (NIT Toyama) SR2024-7		 We develop an indoor location estimation model using Azure Machine Learning (Azure ML) with the goal of establishing an ... [more] SR2024-7
pp.29-33
SR 2024-05-20
16:20		 Kagoshima Yokacenter (Kagoshima)
(Primary: On-site, Secondary: Online)		 Development of an indoor location estimation method using Wi-Fi(2) -- Comparison of Application Implementation on Smartphones --
Takashi Ohkawahara, Yudai Sunagozaka, Rei Hirata, Atsuhi Koizumu, Hiroshi Oguma (NIT Toyama) SR2024-8		 We develop a machine learning model using Azure Machine Learning (Azure ML) to establish an indoor location estimation m... [more] SR2024-8
pp.34-39
SAT, WBS
(Joint)		 2014-05-15
15:35		 Aichi Nagoya Institute of Technology Channel Quality Map Construction Scheme using Multi-GNSS Signals for Heterogeneous Wireless Network
Hiroshi Oguma, Keita Norishima, Atushi Koizumi (TNCT), Fumihiro Yamagata (KNCT), Junpei Kuboniwa, Suguru Kameda, Noriharu Suematsu, Akinori Taira, Tadashi Takagi, Kazuo Tsubouchi (Tohoku Univ.) SAT2014-4		 The multiple network cells are overlapped in the heterogeneous wireless system, the number of networks which users must ... [more] SAT2014-4
pp.17-20
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