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Committee Date Time Place Paper Title / Authors Abstract Paper #
SeMI 2021-01-21
13:00		 Online Online Study on UWB indoor localization method using machine learning-based accurate NLOS detection
Keigo Ishida, Eiji Okamoto (NIT), Huan-Bang Li (NICT) SeMI2020-50		 According to the automatization of factory and other facilities, there is a growing demand of accurate indoor location i... [more] SeMI2020-50
pp.39-44
IT, SIP, RCS 2020-01-23
14:45		 Hiroshima Hiroshima City Youth Center An NLOS sensor elimination method based on estimated position analysis using machine learning in indoor localization
Keigo Ishida, Eiji Okamoto (NIT), Huan-Bang Li (NICT) IT2019-56 SIP2019-69 RCS2019-286		 Indoor location information is getting more and more important in recent years. The localization method using a time of ... [more] IT2019-56 SIP2019-69 RCS2019-286
pp.123-128
MIKA
(2nd)		 2019-10-04
10:15		 Hokkaido Hokkaido Univ. [Poster Presentation] A study on accurate indoor localization in NLOS environments using sensor node selection
Keigo Ishida, Eiji Okamoto (NIT), Huan-Bang Li (NICT) 		Indoor location information is getting more and more important in recent years. The localization method using a time of ... [more]
RCS 2019-06-19
11:20		 Okinawa Miyakojima Hirara Port Terminal Building A study on accurate indoor localization in many NLOS sensor environments
Keigo Ishida, Eiji Okamoto (NIT) RCS2019-47		 Many factories are getting automated, and automated guided vehicles (AGV) have been utilized, where the indoor position ... [more] RCS2019-47
pp.61-66
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