{"id":"https://openalex.org/W4414404673","doi":"https://doi.org/10.1109/tmm.2025.3613144","title":"Semantic Dual-Adversarial Network for Blended-Target Domain Adaptation","display_name":"Semantic Dual-Adversarial Network for Blended-Target Domain Adaptation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414404673","doi":"https://doi.org/10.1109/tmm.2025.3613144"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2025.3613144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3613144","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","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/A5032139219","display_name":"Yuwu Lu","orcid":"https://orcid.org/0000-0003-1215-4915"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuwu Lu","raw_affiliation_strings":["School of Artificial Intelligence, South China Normal University, Foshan, China"],"raw_orcid":"https://orcid.org/0000-0003-1215-4915","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, South China Normal University, Foshan, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011238678","display_name":"Xue Lei Hu","orcid":"https://orcid.org/0009-0001-1027-6065"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xue Hu","raw_affiliation_strings":["School of Artificial Intelligence, South China Normal University, Foshan, China"],"raw_orcid":"https://orcid.org/0009-0001-1027-6065","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, South China Normal University, Foshan, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103027926","display_name":"Haoyu Huang","orcid":"https://orcid.org/0009-0006-5648-4237"},"institutions":[{"id":"https://openalex.org/I187400657","display_name":"South China Normal University","ror":"https://ror.org/01kq0pv72","country_code":"CN","type":"education","lineage":["https://openalex.org/I187400657"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Huang","raw_affiliation_strings":["School of Artificial Intelligence, South China Normal University, Foshan, China"],"raw_orcid":"https://orcid.org/0009-0006-5648-4237","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, South China Normal University, Foshan, China","institution_ids":["https://openalex.org/I187400657"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043352718","display_name":"Zhihui Lai","orcid":"https://orcid.org/0000-0002-4388-3080"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhihui Lai","raw_affiliation_strings":["College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-4388-3080","affiliations":[{"raw_affiliation_string":"College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106943753","display_name":"Xuelong Li","orcid":"https://orcid.org/0000-0003-2924-946X"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210136246","display_name":"China Telecom (China)","ror":"https://ror.org/03jgnzt20","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210136246"]},{"id":"https://openalex.org/I4387153335","display_name":"China Telecom","ror":"https://ror.org/05p67dv18","country_code":null,"type":"company","lineage":["https://openalex.org/I4387153335"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelong Li","raw_affiliation_strings":["Institute of Artificial Intelligence (TeleAI), China Telecom Corporation Ltd, Beijing, China","Institute of Artificial Intelligence (TeleAI), ChinaTelecom Corporation Ltd, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2924-946X","affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence (TeleAI), China Telecom Corporation Ltd, Beijing, China","institution_ids":["https://openalex.org/I4210136246","https://openalex.org/I4387153335"]},{"raw_affiliation_string":"Institute of Artificial Intelligence (TeleAI), ChinaTelecom Corporation Ltd, Beijing, China","institution_ids":["https://openalex.org/I4210100255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.188,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.94315108,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":"27","issue":null,"first_page":"7930","last_page":"7945"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9865999817848206,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9865999817848206,"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/categorical-variable","display_name":"Categorical variable","score":0.611299991607666},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5485000014305115},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.5347999930381775},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.5156000256538391},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.427700012922287},{"id":"https://openalex.org/keywords/extractor","display_name":"Extractor","score":0.4171999990940094},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.40299999713897705},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.39169999957084656}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8762000203132629},{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.611299991607666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6047999858856201},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5485000014305115},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.5347999930381775},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.5156000256538391},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.427700012922287},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.4171999990940094},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40720000863075256},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.39169999957084656},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.388700008392334},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3603000044822693},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34850001335144043},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33399999141693115},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.3287000060081482},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2786000072956085},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.27459999918937683},{"id":"https://openalex.org/C85407183","wikidata":"https://www.wikidata.org/wiki/Q1045785","display_name":"Semantic network","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.2572999894618988},{"id":"https://openalex.org/C193125573","wikidata":"https://www.wikidata.org/wiki/Q7449065","display_name":"Semantic interpretation","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.2513999938964844},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2025.3613144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3613144","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G176027883","display_name":null,"funder_award_id":"2022A1515140099","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G3627583132","display_name":null,"funder_award_id":"2023A1515012875","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"},{"id":"https://openalex.org/G5200290963","display_name":null,"funder_award_id":"62176162","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5293734332","display_name":null,"funder_award_id":"62076129","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"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W4149471","https://openalex.org/W1722318740","https://openalex.org/W2104094955","https://openalex.org/W2131953535","https://openalex.org/W2165698076","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2584009249","https://openalex.org/W2627183927","https://openalex.org/W2741943936","https://openalex.org/W2799166040","https://openalex.org/W2805548989","https://openalex.org/W2904706552","https://openalex.org/W2921304634","https://openalex.org/W2962687275","https://openalex.org/W2962858109","https://openalex.org/W2963506806","https://openalex.org/W2963815618","https://openalex.org/W2963858297","https://openalex.org/W2981720610","https://openalex.org/W2981952612","https://openalex.org/W2984810221","https://openalex.org/W2997739323","https://openalex.org/W3003384866","https://openalex.org/W3007364240","https://openalex.org/W3088032605","https://openalex.org/W3112846941","https://openalex.org/W3118945974","https://openalex.org/W3153166695","https://openalex.org/W3154366079","https://openalex.org/W3157190320","https://openalex.org/W3181434681","https://openalex.org/W3182200686","https://openalex.org/W3183605589","https://openalex.org/W3185386766","https://openalex.org/W3192275354","https://openalex.org/W3204132485","https://openalex.org/W3210474784","https://openalex.org/W3211825525","https://openalex.org/W3212674686","https://openalex.org/W4205474609","https://openalex.org/W4212892254","https://openalex.org/W4213435017","https://openalex.org/W4214623175","https://openalex.org/W4226144843","https://openalex.org/W4281609379","https://openalex.org/W4288064774","https://openalex.org/W4290888597","https://openalex.org/W4292828330","https://openalex.org/W4293222296","https://openalex.org/W4296935214","https://openalex.org/W4311967915","https://openalex.org/W4312246223","https://openalex.org/W4312941859","https://openalex.org/W4315489520","https://openalex.org/W4327852039","https://openalex.org/W4328055065","https://openalex.org/W4365790139","https://openalex.org/W4377000508","https://openalex.org/W4378194787","https://openalex.org/W4382240129","https://openalex.org/W4386057716","https://openalex.org/W4386113268","https://openalex.org/W4386988181","https://openalex.org/W4387272100","https://openalex.org/W4390190864","https://openalex.org/W4390872955","https://openalex.org/W4390938629","https://openalex.org/W4391164226","https://openalex.org/W4391305490","https://openalex.org/W4402727261"],"related_works":[],"abstract_inverted_index":{"The":[0,97],"popularity":[1],"of":[2,42],"blended-target":[3],"domain":[4,33,138,165],"adaptation":[5],"(BTDA)":[6],"is":[7,56,120,127],"growing":[8],"since":[9],"target":[10,36],"data":[11,23],"in":[12,46,197],"the":[13,31,35,91,94,102,107,123,131,159,179,193],"real":[14],"world":[15],"often":[16],"come":[17],"from":[18,30],"multiple":[19,185],"domains":[20,37],"with":[21,144],"different":[22],"distributions.":[24],"Most":[25],"BTDA":[26],"studies":[27],"adapt":[28],"directly":[29],"source":[32,160],"to":[34,61,79,100,110,157,177],"without":[38],"considering":[39],"which":[40,59,162],"kinds":[41],"semantic":[43,54,71,82,118,125],"information":[44,55,119,126],"embedded":[45],"images":[47],"should":[48],"be":[49],"explored.":[50],"Therefore,":[51],"some":[52],"irrelevant":[53,81,117],"inevitably":[57],"used,":[58],"leads":[60],"negative":[62,173],"transfer.":[63],"To":[64,129],"address":[65],"these":[66],"issues,":[67],"we":[68,84,134,149,169],"propose":[69,170],"a":[70,86,136,141,151,171],"dual-adversarial":[72],"network":[73],"(SDN)":[74],"method":[75,176,190],"for":[76],"BTDA.":[77,198],"Specifically,":[78],"suppress":[80],"information,":[83],"adopt":[85],"min-max":[87],"game":[88],"strategy":[89],"between":[90],"classifier":[92,98],"and":[93,122,140],"feature":[95,142,154],"extractor.":[96],"tries":[99],"maximize":[101],"prediction":[103],"distribution":[104],"discrepancy,":[105],"whereas":[106],"extractor":[108,143],"endeavors":[109],"minimize":[111],"this":[112,115],"discrepancy.":[113],"In":[114,147],"process,":[116],"suppressed":[121],"principal":[124],"emphasized.":[128],"align":[130],"categorical":[132],"distributions,":[133],"train":[135],"category-aware":[137],"discriminator":[139],"category":[145],"labels.":[146],"addition,":[148],"introduce":[150],"random":[152],"ratio-based":[153],"fusion":[155],"scheme":[156],"augment":[158],"domain,":[161],"can":[163],"decrease":[164],"gaps.":[166],"At":[167],"last,":[168],"weighted":[172],"self-supervised":[174],"learning":[175],"enhance":[178],"model's":[180],"generalization.":[181],"Extensive":[182],"experiments":[183],"on":[184],"benchmarks":[186],"showcase":[187],"that":[188],"our":[189],"significantly":[191],"outperforms":[192],"prior":[194],"state-of-the-art":[195],"methods":[196]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}