{"id":"https://openalex.org/W4406461837","doi":"https://doi.org/10.1109/bigdata62323.2024.10826134","title":"A Sample-Mixing Unsupervised Domain Adaptation Framework for Object Detection","display_name":"A Sample-Mixing Unsupervised Domain Adaptation Framework for Object Detection","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406461837","doi":"https://doi.org/10.1109/bigdata62323.2024.10826134"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10826134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10826134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5056888567","display_name":"Tianchi Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Tianchi Lin","raw_affiliation_strings":["Beijing Univ. of Posts and Telecom.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Univ. of Posts and Telecom.,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100335246","display_name":"Bo Zhang","orcid":"https://orcid.org/0000-0002-1210-8735"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Zhang","raw_affiliation_strings":["Beijing Univ. of Posts and Telecom.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Univ. of Posts and Telecom.,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100329067","display_name":"Wendong Wang","orcid":"https://orcid.org/0000-0002-6418-8087"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wendong Wang","raw_affiliation_strings":["Beijing Univ. of Posts and Telecom.,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Beijing Univ. of Posts and Telecom.,Beijing,China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056888567"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23848161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3925","last_page":"3930"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9991000294685364,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9940999746322632,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6878177523612976},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.616134524345398},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.5849120020866394},{"id":"https://openalex.org/keywords/mixing","display_name":"Mixing (physics)","score":0.5292030572891235},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5232763886451721},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5010104179382324},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4904803931713104},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4464607834815979},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.41686296463012695},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.33197152614593506},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3186582326889038},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10369464755058289},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06678831577301025},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.052419573068618774}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6878177523612976},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.616134524345398},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.5849120020866394},{"id":"https://openalex.org/C138777275","wikidata":"https://www.wikidata.org/wiki/Q6884054","display_name":"Mixing (physics)","level":2,"score":0.5292030572891235},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5232763886451721},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5010104179382324},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4904803931713104},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4464607834815979},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.41686296463012695},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.33197152614593506},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3186582326889038},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10369464755058289},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06678831577301025},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.052419573068618774},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10826134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10826134","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"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":27,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2102605133","https://openalex.org/W2150066425","https://openalex.org/W2340897893","https://openalex.org/W2955889502","https://openalex.org/W2963037989","https://openalex.org/W2964115968","https://openalex.org/W2964288524","https://openalex.org/W2968634921","https://openalex.org/W2981958729","https://openalex.org/W2982770724","https://openalex.org/W2992308087","https://openalex.org/W2994088087","https://openalex.org/W3034937575","https://openalex.org/W3106723659","https://openalex.org/W3110011650","https://openalex.org/W3118035304","https://openalex.org/W3180426564","https://openalex.org/W3202277637","https://openalex.org/W4212823139","https://openalex.org/W4307823382","https://openalex.org/W4311726887","https://openalex.org/W4386066721","https://openalex.org/W6639480849","https://openalex.org/W6683633756","https://openalex.org/W6770979763","https://openalex.org/W6847876731"],"related_works":["https://openalex.org/W4394775207","https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W3203792196","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W2955455867","https://openalex.org/W4295929828","https://openalex.org/W3156096827"],"abstract_inverted_index":{"Object":[0],"detection":[1,39,85,108,130],"across":[2,149],"diverse":[3,150],"real-world":[4],"environments":[5],"poses":[6],"significant":[7],"challenges":[8],"when":[9,63],"labeled":[10,29,172],"data":[11,22,30],"is":[12,24,31,58],"scarce,":[13],"particularly":[14],"in":[15,116,160],"privacy-sensitive":[16],"scenarios":[17,161],"such":[18,45],"as":[19,46],"healthcare,":[20],"where":[21,162],"annotation":[23,166],"costly":[25],"and":[26,51,94,122,165],"access":[27],"to":[28,67],"often":[32],"restricted.":[33],"In":[34],"healthcare":[35],"settings,":[36],"robust":[37],"human":[38],"systems":[40,159],"can":[41],"enable":[42],"critical":[43],"applications":[44],"patient":[47],"monitoring,":[48],"rehabilitation":[49],"assessment,":[50],"clinical":[52],"workflow":[53],"optimization,":[54],"yet":[55],"their":[56],"deployment":[57],"hindered":[59],"by":[60,106],"domain":[61,80,90,139],"shift":[62],"models":[64],"are":[65],"applied":[66],"new":[68],"environments.":[69],"To":[70],"address":[71],"these":[72],"challenges,":[73],"this":[74],"paper":[75],"presents":[76],"a":[77,100,153],"novel":[78],"unsupervised":[79],"adaptation":[81],"approach":[82,127],"for":[83,156],"object":[84],"that":[86,144],"effectively":[87],"bridges":[88],"the":[89,112,169],"gap":[91],"between":[92],"source":[93],"target":[95,138],"domains.":[96],"Our":[97],"method":[98,146],"introduces":[99],"multi-scale":[101,123],"sample":[102],"mixing":[103,120],"strategy":[104],"guided":[105],"region-level":[107],"confidence":[109],"estimation,":[110],"with":[111],"core":[113],"innovation":[114],"lying":[115],"our":[117,145],"selective":[118],"region":[119],"mechanism":[121],"uncertainty":[124],"estimation.":[125],"This":[126],"enables":[128],"accurate":[129],"of":[131,133,171],"objects":[132],"varying":[134],"sizes":[135],"without":[136],"requiring":[137],"annotations.":[140],"Extensive":[141],"experiments":[142],"demonstrate":[143],"adapts":[147],"robustly":[148],"environments,":[151],"offering":[152],"practical":[154],"solution":[155],"deploying":[157],"AI":[158],"privacy":[163],"concerns":[164],"costs":[167],"limit":[168],"availability":[170],"data.":[173]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
