{"id":"https://openalex.org/W2993271675","doi":"https://doi.org/10.1109/jiot.2019.2956986","title":"Selective Unsupervised Learning-Based Wi-Fi Fingerprint System Using Autoencoder and GAN","display_name":"Selective Unsupervised Learning-Based Wi-Fi Fingerprint System Using Autoencoder and GAN","publication_year":2019,"publication_date":"2019-12-03","ids":{"openalex":"https://openalex.org/W2993271675","doi":"https://doi.org/10.1109/jiot.2019.2956986","mag":"2993271675"},"language":"en","primary_location":{"id":"doi:10.1109/jiot.2019.2956986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2019.2956986","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","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/A5091611912","display_name":"Ju-Hyeon Seong","orcid":"https://orcid.org/0000-0002-8198-0439"},"institutions":[{"id":"https://openalex.org/I197867492","display_name":"Korea Maritime and Ocean University","ror":"https://ror.org/01v7y5b55","country_code":"KR","type":"education","lineage":["https://openalex.org/I197867492"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"J. H. Seong","raw_affiliation_strings":["Advanced IT & Ship Convergence Center, Korea Maritime and Ocean University, Busan, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-8198-0439","affiliations":[{"raw_affiliation_string":"Advanced IT & Ship Convergence Center, Korea Maritime and Ocean University, Busan, South Korea","institution_ids":["https://openalex.org/I197867492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042128313","display_name":"Dong-Hoan Seo","orcid":"https://orcid.org/0000-0003-3610-0356"},"institutions":[{"id":"https://openalex.org/I197867492","display_name":"Korea Maritime and Ocean University","ror":"https://ror.org/01v7y5b55","country_code":"KR","type":"education","lineage":["https://openalex.org/I197867492"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"D. H. Seo","raw_affiliation_strings":["Division of Electronics and Electrical Information Engineering, Korea Maritime and Ocean University, Busan, South Korea"],"raw_orcid":"https://orcid.org/0000-0003-3610-0356","affiliations":[{"raw_affiliation_string":"Division of Electronics and Electrical Information Engineering, Korea Maritime and Ocean University, Busan, South Korea","institution_ids":["https://openalex.org/I197867492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I197867492"],"apc_list":{"value":2045,"currency":"USD","value_usd":2045},"apc_paid":null,"fwci":1.3257,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.80253177,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"7","issue":"3","first_page":"1898","last_page":"1909"},"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/T10860","display_name":"Speech and Audio Processing","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9976000189781189,"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/autoencoder","display_name":"Autoencoder","score":0.9475950002670288},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7811022996902466},{"id":"https://openalex.org/keywords/fingerprint","display_name":"Fingerprint (computing)","score":0.722898542881012},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5367684364318848},{"id":"https://openalex.org/keywords/radio-frequency","display_name":"Radio frequency","score":0.47266969084739685},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4379267990589142},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3892850875854492},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36925357580184937},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10387513041496277}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.9475950002670288},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7811022996902466},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.722898542881012},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5367684364318848},{"id":"https://openalex.org/C74064498","wikidata":"https://www.wikidata.org/wiki/Q3396184","display_name":"Radio frequency","level":2,"score":0.47266969084739685},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4379267990589142},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3892850875854492},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36925357580184937},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10387513041496277}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/jiot.2019.2956986","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jiot.2019.2956986","pdf_url":null,"source":{"id":"https://openalex.org/S2480266640","display_name":"IEEE Internet of Things Journal","issn_l":"2327-4662","issn":["2327-4662","2372-2541"],"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 Internet of Things Journal","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1262416312","display_name":null,"funder_award_id":"2016R1D1A1B03934812","funder_id":"https://openalex.org/F4320321408","funder_display_name":"Ministry of Education"}],"funders":[{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"},{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1981300371","https://openalex.org/W2003738415","https://openalex.org/W2025241138","https://openalex.org/W2099471712","https://openalex.org/W2104228245","https://openalex.org/W2120824934","https://openalex.org/W2134098199","https://openalex.org/W2309512289","https://openalex.org/W2316879520","https://openalex.org/W2342827161","https://openalex.org/W2467200864","https://openalex.org/W2508188811","https://openalex.org/W2517041258","https://openalex.org/W2565419540","https://openalex.org/W2574135915","https://openalex.org/W2599317308","https://openalex.org/W2620149131","https://openalex.org/W2622412670","https://openalex.org/W2623902153","https://openalex.org/W2750575765","https://openalex.org/W2774684174","https://openalex.org/W2778151097","https://openalex.org/W2781518033","https://openalex.org/W2792020330","https://openalex.org/W2793199760","https://openalex.org/W2796050624","https://openalex.org/W2797527950","https://openalex.org/W2797682091","https://openalex.org/W2807857545","https://openalex.org/W2880510969","https://openalex.org/W2891205429","https://openalex.org/W2950364287","https://openalex.org/W2954821101","https://openalex.org/W4320013936","https://openalex.org/W6750629867","https://openalex.org/W6752896642"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2669956259","https://openalex.org/W4249005693","https://openalex.org/W4392946183","https://openalex.org/W3088732000"],"abstract_inverted_index":{"In":[0,60],"this":[1,88],"article,":[2],"we":[3],"propose":[4],"an":[5,12],"automatic":[6],"Wi-Fi":[7,29],"fingerprint":[8],"system":[9,33],"that":[10,52],"combines":[11],"unsupervised":[13],"dual":[14],"radio":[15,47,58,70,80,163,184,203],"mapping":[16],"(UDRM)":[17],"algorithm":[18,51,67,109,141],"with":[19],"the":[20,24,57,61,64,73,78,102,143,147,157,162,171,175,180,183,188,192,197,202],"aim":[21],"of":[22,72,82,146,182,191],"reducing":[23],"time-cost":[25],"needed":[26],"to":[27,101,161,170],"acquire":[28],"signals.":[30],"Our":[31,105,138],"proposed":[32,65,106,139,172],"is":[34,116,168],"appropriate":[35],"for":[36,118,149],"indoor":[37],"environments":[38],"and":[39,55,95,120,155,178,194],"utilizes":[40],"a":[41,69,92,96,126],"minimum":[42],"description":[43],"length":[44],"principle":[45],"(MDLP)-based":[46],"map":[48,71,81,185],"feedback":[49],"(RMF)":[50],"simultaneously":[53],"optimizes":[54,179],"updates":[56],"map.":[59,164,204],"training":[62],"phase,":[63],"UDRM":[66,108],"generates":[68],"entire":[74],"building":[75],"based":[76],"on":[77,130],"measured":[79,151],"one":[83],"reference":[84],"floor.":[85],"It":[86,124],"does":[87,110],"by":[89,186,195],"selectively":[90],"applying":[91],"modified":[93],"autoencoder":[94],"generative":[97],"adversarial":[98],"network":[99],"according":[100],"spatial":[103],"structures.":[104],"learning-based":[107],"not":[111],"require":[112],"labeled":[113],"data,":[114],"which":[115,167],"essential":[117],"supervised":[119],"semisupervised":[121],"learning":[122],"algorithms.":[123],"has":[125],"relatively":[127],"low":[128],"dependence":[129],"received":[131],"signal":[132],"strength":[133],"indicator":[134],"(RSSI)":[135],"data":[136],"sets.":[137],"RMF":[140],"analyzes":[142],"distribution":[144],"characteristics":[145],"RSSIs":[148],"newly":[150,198],"access":[152],"points":[153],"(APs)":[154],"feeds":[156],"analyzed":[158],"results":[159],"back":[160],"The":[165],"MDLP,":[166],"applied":[169],"algorithm,":[173],"improves":[174],"positioning":[176],"performance":[177],"size":[181],"preventing":[187],"indefinite":[189],"updating":[190,196],"RSSI":[193],"added":[199],"APs":[200],"in":[201]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":11}],"updated_date":"2026-08-28T12:50:07.497085","created_date":"2025-10-10T00:00:00"}
