{"id":"https://openalex.org/W4406859874","doi":"https://doi.org/10.1109/vcip63160.2024.10849822","title":"Federated Contrastive Domain Adaptation for Category-inconsistent Object Detection","display_name":"Federated Contrastive Domain Adaptation for Category-inconsistent Object Detection","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4406859874","doi":"https://doi.org/10.1109/vcip63160.2024.10849822"},"language":"en","primary_location":{"id":"doi:10.1109/vcip63160.2024.10849822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849822","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 Visual Communications and Image Processing (VCIP)","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/A5100373301","display_name":"Weiyu Chen","orcid":"https://orcid.org/0000-0002-8206-8388"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]},{"id":"https://openalex.org/I4210107525","display_name":"National Center for High-Performance Computing","ror":"https://ror.org/01jpzd518","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210107525","https://openalex.org/I4210128167","https://openalex.org/I4210166867"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Wei-Yu Chen","raw_affiliation_strings":["National Yang Ming Chiao Tung University,National Center for High-Performance Computing (NCHC),Department of Computer Science,Hsinchu,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University,National Center for High-Performance Computing (NCHC),Department of Computer Science,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I4210107525","https://openalex.org/I148366613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061532856","display_name":"Peggy Joy Lu","orcid":"https://orcid.org/0000-0001-9742-4173"},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Peggy Joy Lu","raw_affiliation_strings":["National Chung Cheng University,Department of Computer Science,Chiayi,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Chung Cheng University,Department of Computer Science,Chiayi,Taiwan","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043399804","display_name":"Vincent S. Tseng","orcid":"https://orcid.org/0000-0002-4853-1594"},"institutions":[{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Vincent Shin-Mu Tseng","raw_affiliation_strings":["National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan"],"affiliations":[{"raw_affiliation_string":"National Yang Ming Chiao Tung University,Department of Computer Science,Hsinchu,Taiwan","institution_ids":["https://openalex.org/I148366613"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100373301"],"corresponding_institution_ids":["https://openalex.org/I148366613","https://openalex.org/I4210107525"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27341678,"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":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.996399998664856,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.996399998664856,"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/T12702","display_name":"Brain Tumor Detection and Classification","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9243000149726868,"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/domain-adaptation","display_name":"Domain adaptation","score":0.8002867102622986},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7696772217750549},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6988216638565063},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5434556007385254},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5274189710617065},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4572969377040863},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4466453194618225},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4195624887943268},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.21987080574035645},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.17886734008789062},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07750847935676575}],"concepts":[{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.8002867102622986},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7696772217750549},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6988216638565063},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5434556007385254},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5274189710617065},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4572969377040863},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4466453194618225},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4195624887943268},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.21987080574035645},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.17886734008789062},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07750847935676575},{"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/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vcip63160.2024.10849822","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vcip63160.2024.10849822","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 Visual Communications and Image Processing (VCIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.41999998688697815,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2150066425","https://openalex.org/W2340897893","https://openalex.org/W2748021867","https://openalex.org/W2963730616","https://openalex.org/W2964115968","https://openalex.org/W2968634921","https://openalex.org/W2981720610","https://openalex.org/W3035564946","https://openalex.org/W3150732979","https://openalex.org/W3176639943","https://openalex.org/W3196371845","https://openalex.org/W3204417859","https://openalex.org/W4214501771","https://openalex.org/W4312935973","https://openalex.org/W4386596927","https://openalex.org/W4393159546","https://openalex.org/W4394593076","https://openalex.org/W6637373629","https://openalex.org/W6728757088","https://openalex.org/W6754770232","https://openalex.org/W6770046221","https://openalex.org/W6772307254","https://openalex.org/W6838694358"],"related_works":["https://openalex.org/W4394775207","https://openalex.org/W4389474468","https://openalex.org/W4300172004","https://openalex.org/W4292830139","https://openalex.org/W4319309705","https://openalex.org/W3203792196","https://openalex.org/W4321649381","https://openalex.org/W2997645659","https://openalex.org/W3180787869","https://openalex.org/W2955455867"],"abstract_inverted_index":{"To":[0],"obtain":[1],"diverse":[2],"scenarios":[3],"for":[4,45,116],"collaboratively":[5],"training":[6],"a":[7,38,53,75],"more":[8],"generalized":[9],"object":[10,16,47],"detector,":[11],"the":[12,50,70,81],"multi-source":[13],"domain":[14,30,97],"adaptive":[15],"detection":[17],"has":[18],"been":[19],"proposed.":[20],"However,":[21],"such":[22],"scenario":[23],"faces":[24],"challenges":[25],"related":[26],"to":[27,61,79],"data":[28],"privacy,":[29],"discrepancy":[31],"and":[32,86,118],"category":[33],"inconsistency,":[34],"thus":[35],"we":[36,73],"propose":[37],"framework":[39],"called":[40],"FedCoin:":[41],"Federated":[42],"Contrastive":[43],"domain-adaptation":[44],"category-inconsistent":[46,117],"detection.":[48],"On":[49,69],"client":[51],"sides,":[52],"novel":[54],"dynamic":[55],"model":[56],"contrastive":[57],"strategy":[58],"is":[59,124],"proposed":[60],"reduce":[62],"excessively":[63],"domain-specific":[64],"features":[65],"from":[66],"local":[67],"models.":[68],"server":[71],"side,":[72],"design":[74],"two-stage":[76],"teacher-student":[77],"architecture":[78],"tackle":[80],"challenge":[82],"of":[83,105],"backbone":[84],"aggregation":[85],"inconsistent":[87],"categories":[88],"integration.":[89],"Our":[90],"method":[91],"outperforms":[92],"SOTA":[93],"methods":[94,115],"across":[95],"different":[96],"adaptation":[98],"tasks,":[99],"with":[100],"an":[101],"average":[102],"precision":[103],"increase":[104],"6%":[106],"on":[107],"various":[108],"datasets,":[109],"demonstrating":[110],"its":[111],"superiority":[112],"over":[113],"existing":[114],"privacy-preserving":[119],"scenarios.":[120],"The":[121],"source":[122],"code":[123],"available":[125],"online:":[126],"https://github.com/ccuvislab/FedCoin":[127]},"counts_by_year":[],"updated_date":"2025-12-22T23:10:17.713674","created_date":"2025-10-10T00:00:00"}
