A Survey on Behavior Recognition Using WiFi Channel State Information

IEEE Communications Magazine

Volumn 55, Issue 10, 2017, Pages 98-104

  Yousefi, Siamak ^a   Narui, Hirokazu ^b,c   Dayal, Sankalp ^d,e   Ermon, Stefano ^c   Valaee, Shahrokh ^a  

^a MCGILL UNIVERSITY   (Canada)

^b Osaka Prefecture University   (Japan)

^c Stanford University   (Japan)

^d INDIAN INSTITUTE OF TECHNOLOGY DELHI   (India)

^e UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BEHAVIORAL RESEARCH; DATA MINING; IMAGE CODING; LEARNING ALGORITHMS; LEARNING SYSTEMS; LONG SHORT-TERM MEMORY; SOCIAL SCIENCES; SURVEYS; WIRELESS LOCAL AREA NETWORKS (WLAN);

BEHAVIOR RECOGNITION; ENVIRONMENT CHANGE; EXTRACTING FEATURES; FRAME RATE SELECTION; HUMAN BEHAVIOR RECOGNITION; LEARNING TECHNIQUES; MACHINE LEARNING TECHNIQUES; MULTI-USER SCENARIO;

CHANNEL STATE INFORMATION;

EID: 85036454840     PISSN: 01636804     EISSN: None     Source Type: Journal    
DOI: 10.1109/MCOM.2017.1700082     Document Type: Article

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