{"id":"https://openalex.org/W4413278232","doi":"https://doi.org/10.1109/icip55913.2025.11084639","title":"New Multi-Source Distributed Transfer Learning Framework","display_name":"New Multi-Source Distributed Transfer Learning Framework","publication_year":2025,"publication_date":"2025-08-18","ids":{"openalex":"https://openalex.org/W4413278232","doi":"https://doi.org/10.1109/icip55913.2025.11084639"},"language":"en","primary_location":{"id":"doi:10.1109/icip55913.2025.11084639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip55913.2025.11084639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5035429304","display_name":"Linqing Huang","orcid":"https://orcid.org/0000-0001-6892-8006"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Linqing Huang","raw_affiliation_strings":["SJTU,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SJTU,Shanghai,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001565555","display_name":"Jing Zhu","orcid":"https://orcid.org/0000-0002-0019-0647"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing Zhu","raw_affiliation_strings":["SJTU,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SJTU,Shanghai,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087014799","display_name":"Yumei Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210147525","display_name":"AviChina Industry & Technology (China)","ror":"https://ror.org/05j26dk60","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210147525"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yumei Hu","raw_affiliation_strings":["AVIC ACTRI,Xi&#x2019;an,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AVIC ACTRI,Xi&#x2019;an,China","institution_ids":["https://openalex.org/I4210147525"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101717684","display_name":"Shilin Wang","orcid":"https://orcid.org/0000-0002-0873-475X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shilin Wang","raw_affiliation_strings":["SJTU,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SJTU,Shanghai,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085695760","display_name":"Gongshen Liu","orcid":"https://orcid.org/0000-0001-5194-1570"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gongshen Liu","raw_affiliation_strings":["SJTU,Shanghai,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SJTU,Shanghai,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047282005","display_name":"Jinfu Fan","orcid":"https://orcid.org/0009-0001-7892-1315"},"institutions":[{"id":"https://openalex.org/I108688024","display_name":"Qingdao University","ror":"https://ror.org/021cj6z65","country_code":"CN","type":"education","lineage":["https://openalex.org/I108688024"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinfu Fan","raw_affiliation_strings":["QDU,Qingdao,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"QDU,Qingdao,China","institution_ids":["https://openalex.org/I108688024"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16965921,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"241","last_page":"246"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.8665000200271606,"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/T12676","display_name":"Machine Learning and ELM","score":0.8665000200271606,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.7468000054359436,"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/computer-science","display_name":"Computer science","score":0.7254081964492798},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5813297629356384},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.36255496740341187},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.25299763679504395}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7254081964492798},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5813297629356384},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.36255496740341187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.25299763679504395}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip55913.2025.11084639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip55913.2025.11084639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309612","display_name":"Natural Science Foundation of Shanghai","ror":null},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2057266281","https://openalex.org/W2089685866","https://openalex.org/W2096943734","https://openalex.org/W2115403315","https://openalex.org/W2344533582","https://openalex.org/W2363300041","https://openalex.org/W2403746960","https://openalex.org/W2406470551","https://openalex.org/W2616287544","https://openalex.org/W2748206084","https://openalex.org/W2912137037","https://openalex.org/W2955547856","https://openalex.org/W2963240485","https://openalex.org/W2963693396","https://openalex.org/W3033245467","https://openalex.org/W3083547659","https://openalex.org/W3091744080","https://openalex.org/W3092500685","https://openalex.org/W3096103439","https://openalex.org/W3145104656","https://openalex.org/W4200092079","https://openalex.org/W4210743024","https://openalex.org/W4301347335","https://openalex.org/W4307392394","https://openalex.org/W4312221027","https://openalex.org/W4312737789","https://openalex.org/W4313480228","https://openalex.org/W4378194787","https://openalex.org/W4380032282","https://openalex.org/W4386824995","https://openalex.org/W4390706868","https://openalex.org/W4400021427","https://openalex.org/W4401568042","https://openalex.org/W4408354173"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"In":[0,54,84],"pattern":[1],"recognition,":[2],"where":[3],"the":[4,27,32,38,79,87,99,141,152],"labeled":[5],"data":[6],"is":[7],"scarce,":[8],"transfer":[9,24],"learning":[10],"(also":[11],"called":[12],"domain":[13,94],"adaptation":[14],"in":[15,151],"some":[16],"cases)":[17],"methods":[18],"frequently":[19],"come":[20],"into":[21],"play":[22],"to":[23,30,69],"knowledge":[25],"from":[26,46],"source":[28,48,76,91,107],"domains":[29,49,77],"bolster":[31],"construction":[33],"of":[34,44,56,81,89,130,137],"classification":[35,52,102,149],"models":[36],"within":[37],"target":[39,93,153],"domain.":[40,154],"The":[41,128],"judicious":[42],"fusion":[43],"information":[45,73],"multiple":[47],"typically":[50],"enhances":[51],"precision.":[53],"light":[55],"this,":[57],"we":[58],"introduce":[59],"a":[60,135],"new":[61],"Multi-source":[62],"Distributed":[63],"Transfer":[64],"Learning":[65],"(MDTL)":[66],"framework":[67],"designed":[68],"adeptly":[70],"integrate":[71],"complementary":[72],"across":[74],"various":[75],"through":[78],"application":[80],"belief":[82,112],"functions.":[83,113],"this":[85],"approach,":[86],"distributions":[88],"each":[90],"and":[92,125,140],"are":[95,109],"aligned":[96],"independently.":[97],"Subsequently,":[98],"resultant":[100],"soft":[101],"outcomes,":[103],"facilitated":[104],"by":[105],"different":[106],"domains,":[108],"amalgamated":[110],"using":[111],"This":[114],"integration":[115],"incorporates":[116],"novel":[117],"weighting":[118],"factors":[119],"that":[120,145],"consider":[121],"both":[122],"distribution":[123],"discrepancies":[124],"classifier":[126],"effectiveness.":[127],"effectiveness":[129],"MDTL":[131],"was":[132],"assessed":[133],"against":[134],"range":[136],"related":[138],"methods,":[139],"experimental":[142],"findings":[143],"confirm":[144],"it":[146],"markedly":[147],"improves":[148],"accuracy":[150]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
