{"id":"https://openalex.org/W2911091942","doi":"https://doi.org/10.1109/tvt.2019.2892563","title":"Enhanced Device-Free Human Detection: Efficient Learning From Phase and Amplitude of Channel State Information","display_name":"Enhanced Device-Free Human Detection: Efficient Learning From Phase and Amplitude of Channel State Information","publication_year":2019,"publication_date":"2019-01-11","ids":{"openalex":"https://openalex.org/W2911091942","doi":"https://doi.org/10.1109/tvt.2019.2892563","mag":"2911091942"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2019.2892563","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2019.2892563","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Vehicular Technology","raw_type":"journal-article"},"type":"article","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/A5038450527","display_name":"Shih\u2010Hau Fang","orcid":"https://orcid.org/0000-0003-1580-0257"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Shih-Hau Fang","raw_affiliation_strings":["Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan"],"raw_orcid":"https://orcid.org/0000-0003-1580-0257","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024745364","display_name":"Chu-Chen Li","orcid":"https://orcid.org/0009-0007-8115-4536"},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Chu-Chen Li","raw_affiliation_strings":["Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027374922","display_name":"Wen-Chen Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I99908691","display_name":"Yuan Ze University","ror":"https://ror.org/01fv1ds98","country_code":"TW","type":"education","lineage":["https://openalex.org/I99908691"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Wen-Chen Lu","raw_affiliation_strings":["Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Yuan Ze University, Taoyuan, Taiwan","institution_ids":["https://openalex.org/I99908691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001791208","display_name":"Zhezhuang Xu","orcid":"https://orcid.org/0000-0001-7535-1575"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhezhuang Xu","raw_affiliation_strings":["School of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7535-1575","affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013301486","display_name":"Ying\u2010Ren Chien","orcid":"https://orcid.org/0000-0002-3013-0290"},"institutions":[{"id":"https://openalex.org/I75430998","display_name":"National Ilan University","ror":"https://ror.org/01npf0s58","country_code":"TW","type":"education","lineage":["https://openalex.org/I75430998"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ying-Ren Chien","raw_affiliation_strings":["Department of Electrical Engineering, National Ilan University, Yilan City, Taiwan"],"raw_orcid":"https://orcid.org/0000-0002-3013-0290","affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, National Ilan University, Yilan City, Taiwan","institution_ids":["https://openalex.org/I75430998"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6953,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.84266686,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"68","issue":"3","first_page":"3048","last_page":"3051"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"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":1.0,"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/T11158","display_name":"Wireless Networks and Protocols","score":0.9922000169754028,"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"}},{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9919000267982483,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7047579288482666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.702133059501648},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6164543032646179},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.5231853127479553},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5090884566307068},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5069146752357483},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.48619741201400757},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4627736806869507},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.44248005747795105},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43311887979507446},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.42235690355300903},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41809841990470886},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3544815182685852},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3514668941497803},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.15034723281860352},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10650911927223206}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7047579288482666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.702133059501648},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6164543032646179},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.5231853127479553},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5090884566307068},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5069146752357483},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.48619741201400757},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4627736806869507},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.44248005747795105},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43311887979507446},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.42235690355300903},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41809841990470886},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3544815182685852},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3514668941497803},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.15034723281860352},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10650911927223206},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2019.2892563","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2019.2892563","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4146623165","display_name":null,"funder_award_id":"MOST 108-2634-F-155-001","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"},{"id":"https://openalex.org/G7726837275","display_name":null,"funder_award_id":"MOST 107-2634-F-155-001","funder_id":"https://openalex.org/F4320322795","funder_display_name":"Ministry of Science and Technology, Taiwan"}],"funders":[{"id":"https://openalex.org/F4320322795","display_name":"Ministry of Science and Technology, Taiwan","ror":"https://ror.org/02kv4zf79"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1503398984","https://openalex.org/W1506806321","https://openalex.org/W1655830068","https://openalex.org/W1665214252","https://openalex.org/W1894623711","https://openalex.org/W2002096058","https://openalex.org/W2002475595","https://openalex.org/W2005059864","https://openalex.org/W2014758824","https://openalex.org/W2040815804","https://openalex.org/W2094147890","https://openalex.org/W2095421215","https://openalex.org/W2105872772","https://openalex.org/W2122687876","https://openalex.org/W2161969291","https://openalex.org/W2163605009","https://openalex.org/W2172292165","https://openalex.org/W2290207474","https://openalex.org/W2309512289","https://openalex.org/W2336963656","https://openalex.org/W2481070470","https://openalex.org/W2558891025","https://openalex.org/W2564039062","https://openalex.org/W2618530766","https://openalex.org/W2743415265","https://openalex.org/W2763522098","https://openalex.org/W6637242042","https://openalex.org/W6696857010"],"related_works":["https://openalex.org/W3090300519","https://openalex.org/W2514492205","https://openalex.org/W4250401876","https://openalex.org/W2943851981","https://openalex.org/W2566526749","https://openalex.org/W3047461507","https://openalex.org/W3126390843","https://openalex.org/W4245880644","https://openalex.org/W4312415459","https://openalex.org/W2528680939"],"abstract_inverted_index":{"With":[0],"the":[1,54,88,91,108,118,141],"rapidly":[2],"increasing":[3],"demand":[4],"for":[5],"security":[6],"and":[7,45,56,71,103,126],"E-health":[8],"applications,":[9],"device-free":[10],"human":[11,40,73],"detection":[12,74,146],"has":[13],"attracted":[14],"interest":[15],"because":[16],"it":[17],"does":[18],"not":[19],"require":[20],"a":[21,30,64],"wearable":[22],"device":[23],"or":[24],"camera":[25],"setup.":[26],"This":[27,51],"paper":[28,52],"proposes":[29],"deep-learning-based":[31],"approach":[32],"that":[33,112,135],"monitors":[34],"wireless":[35],"signals":[36],"to":[37,62],"learn":[38],"three":[39,130],"modes,":[41],"i.e.,":[42],"absence,":[43],"working,":[44],"sleeping,":[46],"in":[47,82],"realistic":[48],"indoor":[49],"environments.":[50],"integrates":[53],"amplitude":[55,152],"phase":[57],"of":[58,90],"channel":[59],"state":[60],"information":[61],"propose":[63],"hybrid":[65,120],"complex":[66],"feature;":[67],"this":[68],"facilitates":[69],"robust":[70],"efficient":[72],"even":[75,128],"with":[76,100,154],"fewer":[77,155],"data":[78],"samples.":[79,139,157],"Experiments":[80],"conducted":[81],"two":[83],"unmodified":[84],"WiFi":[85],"networks":[86,106],"demonstrate":[87],"effectiveness":[89],"proposed":[92,119,142],"algorithms.":[93],"Four":[94],"machine-learning":[95],"algorithms":[96,134],"provide":[97],"satisfactory":[98],"performance":[99],"sufficient":[101],"data,":[102],"deep":[104],"neural":[105],"perform":[107],"best.":[109],"Results":[110],"show":[111],"by":[113,148],"using":[114],"6%":[115],"training":[116,138,156],"samples,":[117],"feature":[121,143,153],"still":[122],"achieves":[123],"93%":[124],"accuracy":[125,147],"can":[127],"outperform":[129],"typical":[131],"machine":[132],"learning":[133],"use":[136],"full":[137],"Moreover,":[140],"significantly":[144],"improves":[145],"11.62%-27.76%":[149],"than":[150],"traditional":[151]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
