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Paper Abstract and Keywords
Presentation 2021-07-16 09:00
A Study on Automatic Labeling MethodUsing Semi-Supervised Learning for Wireless LAN Sensing
Naoki Osumi, Kosuke Tsuji, Ryotaro Isshiki, Yuhei Nagao, Leonardo Lanante, Masayuki Kurosaki, Hiroshi Ochi (Kyutech) RCS2021-93
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, research on CSI (Channel State Information) based wireless sensing using wireless LAN has been gathering attention. CSI sensing is a technology that can be applied to human detection and location estimation by observing channel variations in the surrounding physical environment. In this paper, we analyze the CSI in each surrounding environments using beacon frames that are constantly transmitted from wireless LAN access points. We then focus on semi supervised learning using many unlabeled data and a few labeled data.In this paper, we report a result applying a semi supervised learning method to CSI analysis.
By applying the proposed method, we report that the classification accuracy of more than 90％ was confirmed in person detection and person location estimation by learning from a combination of unlabeled data.
Keyword (in Japanese) (See Japanese page) 
(in English) Wireless LAN Sensing / CSI / Machine Learning / Semi-Supervised Learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 103, RCS2021-93, pp. 74-79, July 2021.
Paper # RCS2021-93 
Date of Issue 2021-07-07 (RCS) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF RCS2021-93

Conference Information
Committee RCS SR NS SeMI RCC  
Conference Date 2021-07-14 - 2021-07-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication and Network Technology of the AI Age, M2M (Machine-to-Machine)，D2D (Device-to-Device)，IoT（Internet of Things）, etc 
Paper Information
Registration To RCS 
Conference Code 2021-07-RCS-SR-NS-SeMI-RCC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Automatic Labeling MethodUsing Semi-Supervised Learning for Wireless LAN Sensing 
Sub Title (in English)  
Keyword(1) Wireless LAN Sensing  
Keyword(2) CSI  
Keyword(3) Machine Learning  
Keyword(4) Semi-Supervised Learning  
Keyword(5)  
Keyword(6)  
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1st Author's Name Naoki Osumi  
1st Author's Affiliation Kyushu Institute of Technology (Kyutech)
2nd Author's Name Kosuke Tsuji  
2nd Author's Affiliation Kyushu Institute of Technology (Kyutech)
3rd Author's Name Ryotaro Isshiki  
3rd Author's Affiliation Kyushu Institute of Technology (Kyutech)
4th Author's Name Yuhei Nagao  
4th Author's Affiliation Kyushu Institute of Technology (Kyutech)
5th Author's Name Leonardo Lanante  
5th Author's Affiliation Kyushu Institute of Technology (Kyutech)
6th Author's Name Masayuki Kurosaki  
6th Author's Affiliation Kyushu Institute of Technology (Kyutech)
7th Author's Name Hiroshi Ochi  
7th Author's Affiliation Kyushu Institute of Technology (Kyutech)
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Speaker Author-1 
Date Time 2021-07-16 09:00:00 
Presentation Time 25 minutes 
Registration for RCS 
Paper # RCS2021-93 
Volume (vol) vol.121 
Number (no) no.103 
Page pp.74-79 
#Pages 6 
Date of Issue 2021-07-07 (RCS) 

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