{"id":"https://openalex.org/W4280520421","doi":"https://doi.org/10.1109/icc45855.2022.9839011","title":"Quantum Transfer Learning for Wi-Fi Sensing","display_name":"Quantum Transfer Learning for Wi-Fi Sensing","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4280520421","doi":"https://doi.org/10.1109/icc45855.2022.9839011"},"language":"en","primary_location":{"id":"doi:10.1109/icc45855.2022.9839011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023338067","display_name":"Toshiaki Koike\u2013Akino","orcid":"https://orcid.org/0000-0002-2578-5372"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Toshiaki Koike-Akino","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA,02139"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA,02139","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100383518","display_name":"Pu Wang","orcid":"https://orcid.org/0000-0002-4718-3102"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Pu Wang","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA,02139"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA,02139","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100423404","display_name":"Ye Wang","orcid":"https://orcid.org/0000-0001-5220-1830"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ye Wang","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA,02139"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL),Cambridge,MA,USA,02139","institution_ids":["https://openalex.org/I4210159266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210159266"],"apc_list":null,"apc_paid":null,"fwci":7.0212,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.98308527,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"654","last_page":"659"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.9962000250816345,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.7874509692192078},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.781765341758728},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.6595559120178223},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.6181309819221497},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5159597992897034},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5078132748603821},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4468843340873718},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4383721649646759},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4224241375923157},{"id":"https://openalex.org/keywords/quantum","display_name":"Quantum","score":0.41099220514297485},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.37814486026763916},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.2589799165725708}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.7874509692192078},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.781765341758728},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6595559120178223},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.6181309819221497},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5159597992897034},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5078132748603821},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4468843340873718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4383721649646759},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4224241375923157},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.41099220514297485},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.37814486026763916},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2589799165725708},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc45855.2022.9839011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc45855.2022.9839011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2022 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W1568345435","https://openalex.org/W1891910822","https://openalex.org/W2007787077","https://openalex.org/W2016549506","https://openalex.org/W2103956991","https://openalex.org/W2527142536","https://openalex.org/W2539677907","https://openalex.org/W2562234976","https://openalex.org/W2611540227","https://openalex.org/W2749809371","https://openalex.org/W2755255888","https://openalex.org/W2786808285","https://openalex.org/W2788518751","https://openalex.org/W2794444783","https://openalex.org/W2796293949","https://openalex.org/W2798945316","https://openalex.org/W2798967590","https://openalex.org/W2799062425","https://openalex.org/W2809191403","https://openalex.org/W2827033964","https://openalex.org/W2886933259","https://openalex.org/W2888228864","https://openalex.org/W2903221501","https://openalex.org/W2921920881","https://openalex.org/W2929612105","https://openalex.org/W2938514801","https://openalex.org/W2947173962","https://openalex.org/W2949860773","https://openalex.org/W2952065976","https://openalex.org/W2954939433","https://openalex.org/W2963809228","https://openalex.org/W2975305172","https://openalex.org/W2977042651","https://openalex.org/W2979856235","https://openalex.org/W2981031975","https://openalex.org/W2981892815","https://openalex.org/W2982169647","https://openalex.org/W2995742898","https://openalex.org/W2996856852","https://openalex.org/W3007475506","https://openalex.org/W3009202881","https://openalex.org/W3009570630","https://openalex.org/W3010023800","https://openalex.org/W3010205642","https://openalex.org/W3021587713","https://openalex.org/W3022862112","https://openalex.org/W3098599423","https://openalex.org/W3104022488","https://openalex.org/W3104396616","https://openalex.org/W3105380624","https://openalex.org/W3106367563","https://openalex.org/W3107463944","https://openalex.org/W3124082267","https://openalex.org/W3129252918","https://openalex.org/W3134524169","https://openalex.org/W3136233239","https://openalex.org/W4253510307","https://openalex.org/W4298109276","https://openalex.org/W4300988299","https://openalex.org/W6634007516","https://openalex.org/W6697071954","https://openalex.org/W6748683284","https://openalex.org/W6767983773","https://openalex.org/W6789376099"],"related_works":["https://openalex.org/W4206357785","https://openalex.org/W4281381188","https://openalex.org/W3192840557","https://openalex.org/W2951211570","https://openalex.org/W4375928479","https://openalex.org/W3167935049","https://openalex.org/W3023427754","https://openalex.org/W3131673289","https://openalex.org/W4393011546","https://openalex.org/W3198847674"],"abstract_inverted_index":{"Beyond":[0],"data":[1,125],"communications,":[2],"commercial-off-the-shelf":[3],"Wi-Fi":[4,70],"devices":[5],"can":[6],"be":[7,39],"used":[8],"to":[9,38,61],"monitor":[10],"human":[11,66,114],"activities,":[12],"track":[13],"device":[14],"locomotion,":[15],"and":[16,45,72,105],"sense":[17],"the":[18,31,96],"ambient":[19],"environment.":[20],"In":[21,54],"particular,":[22],"spatial":[23],"beam":[24],"attributes":[25],"that":[26],"are":[27],"inherently":[28],"available":[29],"in":[30,41,65],"60-GHz":[32],"IEEE":[33],"802.11ad/ay":[34],"standards":[35],"have":[36],"shown":[37],"effective":[40],"terms":[42],"of":[43,102],"overhead":[44],"channel":[46],"measurement":[47],"granularity":[48],"for":[49,95,113],"these":[50],"indoor":[51],"sensing":[52],"tasks.":[53],"this":[55],"paper,":[56],"we":[57,81],"investigate":[58],"transfer":[59],"learning":[60],"mitigate":[62],"domain":[63],"shift":[64],"monitoring":[67],"tasks":[68],"when":[69],"settings":[71],"environments":[73],"change":[74],"over":[75],"time.":[76],"As":[77],"a":[78,123],"proof-of-concept":[79],"study,":[80],"consider":[82],"quantum":[83],"neural":[84,92],"networks":[85,93],"(QNN)":[86],"as":[87,89],"well":[88],"classical":[90],"deep":[91],"(DNN)":[94],"future":[97],"quantum-ready":[98],"society.":[99],"The":[100],"effectiveness":[101],"both":[103],"DNN":[104],"QNN":[106],"is":[107],"validated":[108],"by":[109],"an":[110],"in-house":[111],"experiment":[112],"pose":[115],"recognition,":[116],"achieving":[117],"greater":[118],"than":[119],"90%":[120],"accuracy":[121],"with":[122],"limited":[124],"size.":[126]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
