{"id":"https://openalex.org/W4416251626","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228496","title":"Dual-Domain Discriminative Learning with Joint Consistency for Domain Adaptation","display_name":"Dual-Domain Discriminative Learning with Joint Consistency for Domain Adaptation","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251626","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228496"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228496","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228496","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5107934499","display_name":"Z. Ning","orcid":"https://orcid.org/0009-0005-7618-7662"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhenyang Ning","raw_affiliation_strings":["Guangdong University of Technology,School of Computer Science and Technology,GuangZhou,China,511400"],"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology,School of Computer Science and Technology,GuangZhou,China,511400","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003969171","display_name":"Shaohua Teng","orcid":"https://orcid.org/0000-0002-7204-1288"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohua Teng","raw_affiliation_strings":["Guangdong University of Technology,School of Computer Science and Technology,GuangZhou,China,511400"],"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology,School of Computer Science and Technology,GuangZhou,China,511400","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116592770","display_name":"Zefeng Zheng","orcid":"https://orcid.org/0000-0003-1324-7398"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zefeng Zheng","raw_affiliation_strings":["Guangdong University of Technology,School of Computer Science and Technology,GuangZhou,China,511400"],"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology,School of Computer Science and Technology,GuangZhou,China,511400","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100349334","display_name":"Wei Zhang","orcid":"https://orcid.org/0000-0003-2747-1622"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Zhang","raw_affiliation_strings":["Guangdong University of Technology,School of Computer Science and Technology,GuangZhou,China,511400"],"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology,School of Computer Science and Technology,GuangZhou,China,511400","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110974108","display_name":"Yihang Dong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihang Dong","raw_affiliation_strings":["University of Chinese Academy of Sciences,Beijing,China,101408"],"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences,Beijing,China,101408","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5107934499"],"corresponding_institution_ids":["https://openalex.org/I139024713"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19483931,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9904000163078308,"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":0.9904000163078308,"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/T11448","display_name":"Face recognition and analysis","score":0.0007999999797903001,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11550","display_name":"Text and Document Classification Technologies","score":0.000699999975040555,"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/discriminative-model","display_name":"Discriminative model","score":0.9362000226974487},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5623000264167786},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5217000246047974},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5126000046730042},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4749000072479248},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.46639999747276306},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4618000090122223},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.45730000734329224}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9362000226974487},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6837000250816345},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6809999942779541},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5627999901771545},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5623000264167786},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5217000246047974},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5126000046730042},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4749000072479248},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.46639999747276306},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4618000090122223},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.45730000734329224},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4422999918460846},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4325000047683716},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.3495999872684479},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.3346000015735626},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.31040000915527344},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3041999936103821},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.30250000953674316},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.30070000886917114}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228496","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228496","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1722318740","https://openalex.org/W2104094955","https://openalex.org/W2125865219","https://openalex.org/W2131953535","https://openalex.org/W2194775991","https://openalex.org/W2627183927","https://openalex.org/W2786808285","https://openalex.org/W2962687275","https://openalex.org/W2969985801","https://openalex.org/W2998459790","https://openalex.org/W3021632667","https://openalex.org/W3035519852","https://openalex.org/W3040932449","https://openalex.org/W4233762729","https://openalex.org/W4285107695","https://openalex.org/W4295908664","https://openalex.org/W4313427650","https://openalex.org/W4318459969","https://openalex.org/W4319299795","https://openalex.org/W4367057008","https://openalex.org/W4385488928","https://openalex.org/W4385764641","https://openalex.org/W4389331429","https://openalex.org/W4390191228","https://openalex.org/W4390871753","https://openalex.org/W4391953425","https://openalex.org/W4393148449","https://openalex.org/W4401554449","https://openalex.org/W4401656685","https://openalex.org/W4403136854","https://openalex.org/W4403791273","https://openalex.org/W4403792044","https://openalex.org/W4404007442","https://openalex.org/W4404788554","https://openalex.org/W4405950485","https://openalex.org/W4406110380","https://openalex.org/W4406259909","https://openalex.org/W4406260074","https://openalex.org/W4406261673","https://openalex.org/W4406391458","https://openalex.org/W4406612503","https://openalex.org/W4407743259","https://openalex.org/W4408354263","https://openalex.org/W4409261976","https://openalex.org/W4409365102","https://openalex.org/W4412511526","https://openalex.org/W4415795314"],"related_works":[],"abstract_inverted_index":{"Domain":[0],"adaptation":[1],"(DA)":[2],"is":[3,112],"designed":[4],"to":[5,19,58,85,114,128],"tackle":[6],"the":[7,13,86,94,117,124,130,135,150],"problem":[8],"of":[9,34,41,137],"label":[10],"scarcity":[11],"in":[12,27],"target":[14,95],"domain":[15,88],"by":[16],"transferring":[17],"knowledge":[18],"it.":[20],"However,":[21],"there":[22],"are":[23,142],"two":[24,65],"critical":[25],"challenges":[26],"DA":[28],":":[29],"1)":[30],"insufficient":[31],"discriminative":[32,100],"power":[33],"learned":[35],"features,":[36],"and":[37,72,126,149],"2)":[38],"inadequate":[39],"exploration":[40],"inter-sample":[42],"relationships.":[43],"This":[44,62,121],"study":[45],"proposes":[46],"a":[47,98,107],"novel":[48,108],"framework,":[49],"Joint":[50,73],"Consistency-Driven":[51],"Dual-Domain":[52],"Discriminative":[53],"Learning":[54],"(JCD<sup":[55],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[56],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">3</sup>L)":[57],"overcome":[59],"these":[60],"limitations.":[61],"framework":[63],"encompasses":[64],"components:":[66],"Inter-domain":[67],"Collaborative":[68],"Feature":[69],"Enhancement":[70],"(ID-CFE)":[71],"Semantic-Spatial":[74],"Consistency":[75],"Constraint":[76],"(JSSCC).":[77],"Firstly,":[78],"ID-CFE":[79],"applies":[80],"angular":[81],"margin":[82],"(AM)":[83],"loss":[84],"source":[87],"while":[89],"imposing":[90],"entropy":[91],"regularization":[92,122],"on":[93],"domain,":[96],"establishing":[97],"dual-domain":[99],"enhancement":[101],"mechanism":[102],"for":[103],"feature":[104],"representations.":[105],"Additionally,":[106],"consistency":[109],"regularization,":[110],"JSSCC,":[111],"proposed":[113],"thoroughly":[115],"explore":[116],"interrelationships":[118],"among":[119],"samples.":[120],"leverages":[123],"label-semantics":[125],"feature-semantics":[127],"refine":[129],"alignment":[131],"process.":[132],"To":[133],"verify":[134],"effectiveness":[136],"our":[138],"work,":[139],"comprehensive":[140],"experiments":[141],"conducted":[143],"across":[144],"three":[145],"widely":[146],"used":[147],"benchmarks":[148],"results":[151],"demonstrate":[152],"considerable":[153],"improvements.":[154]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}
