{"id":"https://openalex.org/W4402125799","doi":"https://doi.org/10.3390/s24175698","title":"Wi-Fi Fingerprint Indoor Localization by Semi-Supervised Generative Adversarial Network","display_name":"Wi-Fi Fingerprint Indoor Localization by Semi-Supervised Generative Adversarial Network","publication_year":2024,"publication_date":"2024-09-01","ids":{"openalex":"https://openalex.org/W4402125799","doi":"https://doi.org/10.3390/s24175698","pmid":"https://pubmed.ncbi.nlm.nih.gov/39275609"},"language":"en","primary_location":{"id":"doi:10.3390/s24175698","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24175698","pdf_url":"https://www.mdpi.com/1424-8220/24/17/5698/pdf?version=1725185031","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/24/17/5698/pdf?version=1725185031","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055716467","display_name":"Jaehyun Yoo","orcid":"https://orcid.org/0000-0002-6167-2842"},"institutions":[{"id":"https://openalex.org/I165677929","display_name":"Sungshin Women's University","ror":"https://ror.org/0500xzf72","country_code":"KR","type":"education","lineage":["https://openalex.org/I165677929"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jaehyun Yoo","raw_affiliation_strings":["School of AI Convergence, Sungshin Women\u2019s University, 34 da-gil 2, Bomun-ro, Seongbuk-gu, Seoul 02844, Republic of Korea","School of AI Convergence, Sungshin Women's University, 34 da-gil 2, Bomun-ro, Seongbuk-gu, Seoul 02844, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-6167-2842","affiliations":[{"raw_affiliation_string":"School of AI Convergence, Sungshin Women\u2019s University, 34 da-gil 2, Bomun-ro, Seongbuk-gu, Seoul 02844, Republic of Korea","institution_ids":["https://openalex.org/I165677929"]},{"raw_affiliation_string":"School of AI Convergence, Sungshin Women's University, 34 da-gil 2, Bomun-ro, Seongbuk-gu, Seoul 02844, Republic of Korea","institution_ids":["https://openalex.org/I165677929"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5055716467"],"corresponding_institution_ids":["https://openalex.org/I165677929"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.4786,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.82428229,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"24","issue":"17","first_page":"5698","last_page":"5698"},"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":0.9991999864578247,"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":0.9955000281333923,"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/fingerprint","display_name":"Fingerprint (computing)","score":0.7963827848434448},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.75464928150177},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.692026674747467},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6144497990608215},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.543557345867157},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5377979278564453},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4833947718143463},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4754188656806946},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.43556833267211914},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37537434697151184},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35300880670547485}],"concepts":[{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.7963827848434448},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.75464928150177},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.692026674747467},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6144497990608215},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.543557345867157},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5377979278564453},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4833947718143463},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4754188656806946},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.43556833267211914},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37537434697151184},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35300880670547485},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s24175698","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24175698","pdf_url":"https://www.mdpi.com/1424-8220/24/17/5698/pdf?version=1725185031","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:39275609","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/39275609","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:11398001","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/11398001","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11398001/pdf/sensors-24-05698.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:24f87dbc05bf44f8ad8b8ed0129055d0","is_oa":false,"landing_page_url":"https://doaj.org/article/24f87dbc05bf44f8ad8b8ed0129055d0","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 24, Iss 17, p 5698 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s24175698","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s24175698","pdf_url":"https://www.mdpi.com/1424-8220/24/17/5698/pdf?version=1725185031","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.46000000834465027,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4402125799.pdf","grobid_xml":"https://content.openalex.org/works/W4402125799.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W2072158021","https://openalex.org/W2739748921","https://openalex.org/W2745157305","https://openalex.org/W2756340466","https://openalex.org/W2769039670","https://openalex.org/W2907301012","https://openalex.org/W2962805368","https://openalex.org/W2984128863","https://openalex.org/W2993271675","https://openalex.org/W3004986376","https://openalex.org/W3006247566","https://openalex.org/W3011286333","https://openalex.org/W3040218637","https://openalex.org/W3121381145","https://openalex.org/W4224213019","https://openalex.org/W4303981251","https://openalex.org/W4320013936","https://openalex.org/W4367598753","https://openalex.org/W4390422140","https://openalex.org/W4390670517","https://openalex.org/W4392371175","https://openalex.org/W6735913928"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2339806289","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W2368132270","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W3182931000","https://openalex.org/W4389345324"],"abstract_inverted_index":{"Wi-Fi":[0,5,47,62,86,103,121],"fingerprint":[1,59,87],"indoor":[2],"localization":[3],"uses":[4],"signal":[6],"strength":[7],"measurements":[8],"obtained":[9],"from":[10,73],"a":[11,23,46,67,76,97,107,115,126,134,142],"number":[12],"of":[13],"access":[14],"points.":[15],"This":[16],"method":[17],"needs":[18],"manual":[19],"data":[20,94],"collection":[21],"across":[22],"positioning":[24,108,117],"area":[25],"and":[26,41],"an":[27],"annotation":[28],"process":[29],"to":[30,33,83,92,125,141],"label":[31],"locations":[32],"the":[34,39,101,120,130],"measurement":[35],"sets.":[36],"To":[37],"reduce":[38],"cost":[40],"effort,":[42],"this":[43],"paper":[44],"proposes":[45],"Semi-Supervised":[48],"Generative":[49],"Adversarial":[50],"Network":[51],"(SSGAN),":[52],"which":[53,70,89],"produces":[54],"artificial":[55],"but":[56],"realistic":[57],"trainable":[58],"data.":[60],"The":[61],"SSGAN":[63,104,122],"is":[64,71,81,90,123],"based":[65],"on":[66],"deep":[68,145],"learning,":[69],"extended":[72],"GAN":[74],"in":[75,139],"semi-supervised":[77],"learning":[78],"manner.":[79],"It":[80],"designed":[82],"create":[84],"location-labeled":[85],"data,":[88],"different":[91],"unlabeled":[93],"generation":[95],"by":[96],"normal":[98],"GAN.":[99],"Also,":[100],"proposed":[102],"network":[105],"includes":[106],"model,":[109],"so":[110],"it":[111],"does":[112],"not":[113],"need":[114],"external":[116],"method.":[118],"When":[119],"applied":[124],"multi-story":[127],"landmark":[128],"localization,":[129],"experimental":[131],"results":[132],"demonstrate":[133],"35%":[135],"more":[136],"accurate":[137],"performance":[138],"comparison":[140],"standard":[143],"supervised":[144],"neural":[146],"network.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":8}],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}