{"id":"https://openalex.org/W4414982790","doi":"https://doi.org/10.1109/tnnls.2025.3616236","title":"FGPLFA: Fine-Grained Pseudo-Labeling and Feature Alignment for Source-Free Unsupervised Domain Adaptation","display_name":"FGPLFA: Fine-Grained Pseudo-Labeling and Feature Alignment for Source-Free Unsupervised Domain Adaptation","publication_year":2025,"publication_date":"2025-10-07","ids":{"openalex":"https://openalex.org/W4414982790","doi":"https://doi.org/10.1109/tnnls.2025.3616236","pmid":"https://pubmed.ncbi.nlm.nih.gov/41056156"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2025.3616236","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3616236","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5108058685","display_name":"Zhongyi Wen","orcid":"https://orcid.org/0000-0003-4999-3982"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyi Wen","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-4999-3982","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qiang Li","orcid":"https://orcid.org/0000-0001-5609-3320"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Li","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-5609-3320","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036560410","display_name":"Yatong Wang","orcid":"https://orcid.org/0000-0001-9887-5224"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yatong Wang","raw_affiliation_strings":["School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9887-5224","affiliations":[{"raw_affiliation_string":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049429193","display_name":"Huaizong Shao","orcid":"https://orcid.org/0000-0003-1253-7991"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huaizong Shao","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-1253-7991","affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051081481","display_name":"Guoming Sun","orcid":"https://orcid.org/0000-0003-0818-4708"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guoming Sun","raw_affiliation_strings":["School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.792,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91809305,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"37","issue":"3","first_page":"1332","last_page":"1346"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9696000218391418,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9696000218391418,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10201","display_name":"Speech Recognition and Synthesis","score":0.9527000188827515,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.6057999730110168},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6000000238418579},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5935999751091003},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5350000262260437},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5245000123977661},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5212000012397766},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5109000205993652},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4643999934196472}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7796000242233276},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6129000186920166},{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.6057999730110168},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6000000238418579},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5935999751091003},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5835999846458435},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5350000262260437},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5245000123977661},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5212000012397766},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4643999934196472},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.42640000581741333},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4244999885559082},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.39329999685287476},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.3280999958515167},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C66696666","wikidata":"https://www.wikidata.org/wiki/Q17105612","display_name":"Sample entropy","level":3,"score":0.30410000681877136},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.2750999927520752},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2025.3616236","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2025.3616236","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:41056156","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41056156","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":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5700301572","display_name":null,"funder_award_id":"62171110","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6915201568","display_name":null,"funder_award_id":"62401052","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7117616998","display_name":null,"funder_award_id":"62301115","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Source-free":[0],"unsupervised":[1],"domain":[2,12,17,143],"adaptation":[3],"(SFUDA)":[4],"aims":[5],"to":[6,28,77],"improve":[7],"performance":[8],"in":[9,22,54,170,177],"unlabeled":[10],"target":[11,179],"data":[13,51,95,117],"without":[14],"accessing":[15],"source":[16],"data.":[18],"This":[19,114],"is":[20],"crucial":[21],"scenarios":[23],"with":[24,83,140],"data-sharing":[25],"restrictions":[26],"due":[27],"privacy":[29],"or":[30,44],"compliance":[31],"constraints.":[32],"Existing":[33],"SFUDA":[34],"approaches":[35],"often":[36,48],"rely":[37],"on":[38,42,119],"pseudo-labeling":[39,72,109],"techniques":[40],"based":[41,118],"entropy":[43],"confidence":[45],"metrics.":[46],"These":[47],"overlook":[49],"fine-grained":[50,71,108],"features,":[52,96],"resulting":[53],"noisy":[55,152],"pseudo-labels":[56],"that":[57,87,150],"degrade":[58],"model":[59,92,175],"performance.":[60,80],"To":[61,103],"overcome":[62],"this":[63],"limitation,":[64],"we":[65],"develop":[66],"a":[67,84,98,146,171],"new":[68],"method":[69,161],"called":[70],"and":[73,94,122,142],"feature":[74,158],"alignment":[75,159],"(FGPLFA)":[76],"enhance":[78,104],"SFUDA's":[79],"FGPLFA":[81],"starts":[82],"gradient-based":[85],"metric":[86],"integrates":[88],"insights":[89],"from":[90,165],"both":[91],"knowledge":[93],"creating":[97],"more":[99],"reliable":[100],"sample":[101,134],"metric.":[102],"fine":[105],"granularity,":[106],"the":[107,120,133,155,166,178,188],"(FGPL)":[110],"module":[111,115],"was":[112,162],"introduced.":[113,163],"clusters":[116],"magnitude":[121],"direction":[123],"of":[124,190],"gradients,":[125],"allowing":[126],"for":[127],"dataset":[128],"partitioning":[129],"into":[130],"subsets":[131,137,167],"at":[132],"level.":[135],"The":[136],"are":[138,168],"pseudo-labeled":[139],"category-specificity":[141],"specificity,":[144],"establishing":[145],"multilevel":[147],"granularity":[148],"structure":[149],"reduces":[151],"pseudo-labels.":[153],"Subsequently,":[154],"mean-covariance":[156],"adjustment":[157],"(MCAFA)":[160],"Features":[164],"aligned":[169],"specified":[172],"sequence,":[173],"enhancing":[174],"adaptability":[176],"domain.":[180],"Extensive":[181],"experiments":[182],"conducted":[183],"across":[184],"multiple":[185],"datasets":[186],"validate":[187],"superiority":[189],"FGPLFA.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-03T06:13:14.889584","created_date":"2025-10-10T00:00:00"}