{"id":"https://openalex.org/W4416250172","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227862","title":"Adaptive Weighted Triplet Loss with CBAM Integration for Federated Learning","display_name":"Adaptive Weighted Triplet Loss with CBAM Integration for Federated Learning","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250172","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227862"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227862","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":"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/A5082076229","display_name":"Mingzhen Wang","orcid":"https://orcid.org/0000-0002-4852-9443"},"institutions":[{"id":"https://openalex.org/I4210158570","display_name":"Zhejiang University-University of Edinburgh Institute","ror":"https://ror.org/04jth1r26","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210158570","https://openalex.org/I76130692","https://openalex.org/I98677209"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhen Wang","raw_affiliation_strings":["Zhejiang University,ZJU-UIUC Institute,Haining,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,ZJU-UIUC Institute,Haining,China","institution_ids":["https://openalex.org/I4210158570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026018838","display_name":"Ying Tu","orcid":"https://orcid.org/0000-0001-7770-9876"},"institutions":[{"id":"https://openalex.org/I1300757298","display_name":"Heilongjiang University of Science and Technology","ror":"https://ror.org/030xwyx96","country_code":"CN","type":"education","lineage":["https://openalex.org/I1300757298"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanjie Tu","raw_affiliation_strings":["Heilongjiang University of Science and Technology,School of Computer and Information Engineering,Harbin,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heilongjiang University of Science and Technology,School of Computer and Information Engineering,Harbin,China","institution_ids":["https://openalex.org/I1300757298"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084513745","display_name":"C. Z. Yuan","orcid":"https://orcid.org/0009-0004-6507-0496"},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"ChunHong Yuan","raw_affiliation_strings":["Kazan (Volga Region) Federal University,Department of Pre-Engineering,Kazan,Russia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kazan (Volga Region) Federal University,Department of Pre-Engineering,Kazan,Russia","institution_ids":["https://openalex.org/I21203515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084824459","display_name":"Kaiming Liu","orcid":"https://orcid.org/0000-0001-6006-3239"},"institutions":[{"id":"https://openalex.org/I4210158318","display_name":"Second Affiliated Hospital of Zhejiang University","ror":"https://ror.org/059cjpv64","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210158318"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaiming Liu","raw_affiliation_strings":["Zhejiang University,Second Affiliated Hospital, School of Medicine,Department of Neurology,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,Second Affiliated Hospital, School of Medicine,Department of Neurology,Hangzhou,China","institution_ids":["https://openalex.org/I4210158318"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042940038","display_name":"Hao Jin","orcid":"https://orcid.org/0000-0001-9798-5149"},"institutions":[{"id":"https://openalex.org/I4210158570","display_name":"Zhejiang University-University of Edinburgh Institute","ror":"https://ror.org/04jth1r26","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210158570","https://openalex.org/I76130692","https://openalex.org/I98677209"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Jin","raw_affiliation_strings":["Zhejiang University,ZJU-UIUC Institute,Haining,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,ZJU-UIUC Institute,Haining,China","institution_ids":["https://openalex.org/I4210158570"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9164999723434448,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9164999723434448,"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/T13918","display_name":"Advanced Data and IoT Technologies","score":0.009499999694526196,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10237","display_name":"Cryptography and Data Security","score":0.006599999964237213,"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/flexibility","display_name":"Flexibility (engineering)","score":0.7856000065803528},{"id":"https://openalex.org/keywords/server","display_name":"Server","score":0.6930999755859375},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6101999878883362},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.505299985408783},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.5012000203132629},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.49630001187324524},{"id":"https://openalex.org/keywords/federated-learning","display_name":"Federated learning","score":0.46050000190734863},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4237000048160553},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.38989999890327454}],"concepts":[{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.7856000065803528},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7297000288963318},{"id":"https://openalex.org/C93996380","wikidata":"https://www.wikidata.org/wiki/Q44127","display_name":"Server","level":2,"score":0.6930999755859375},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6101999878883362},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.505299985408783},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.5012000203132629},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.49630001187324524},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.46050000190734863},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4415999948978424},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4237000048160553},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3955000042915344},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.38989999890327454},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3644999861717224},{"id":"https://openalex.org/C70061542","wikidata":"https://www.wikidata.org/wiki/Q989016","display_name":"Distributed database","level":2,"score":0.350600004196167},{"id":"https://openalex.org/C153740404","wikidata":"https://www.wikidata.org/wiki/Q671224","display_name":"Data center","level":2,"score":0.3497999906539917},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3296999931335449},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.3156999945640564},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30300000309944153},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.299699991941452},{"id":"https://openalex.org/C123201435","wikidata":"https://www.wikidata.org/wiki/Q456632","display_name":"Information privacy","level":2,"score":0.2935999929904938},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.2827000021934509},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27239999175071716},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.25870001316070557},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C182590292","wikidata":"https://www.wikidata.org/wiki/Q989632","display_name":"Network security","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227862","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227862","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":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1909903157","https://openalex.org/W2096733369","https://openalex.org/W2112796928","https://openalex.org/W2735158786","https://openalex.org/W2884585870","https://openalex.org/W2894568782","https://openalex.org/W3200947677","https://openalex.org/W3207668590","https://openalex.org/W3212386989","https://openalex.org/W3212708089","https://openalex.org/W3217228024","https://openalex.org/W4220694836","https://openalex.org/W4226224676","https://openalex.org/W4283275666","https://openalex.org/W4292793982","https://openalex.org/W4293155325","https://openalex.org/W4296122752","https://openalex.org/W4302275239","https://openalex.org/W4312258849","https://openalex.org/W4312505280","https://openalex.org/W4319336142","https://openalex.org/W4379382445","https://openalex.org/W4379879286","https://openalex.org/W4380992649","https://openalex.org/W4386066416","https://openalex.org/W4386072282","https://openalex.org/W4389252620","https://openalex.org/W4404412056"],"related_works":[],"abstract_inverted_index":{"The":[0],"Triplet":[1,41,80,121,149,156,168,185],"Network":[2,81,122,150,186],"has":[3,85],"made":[4],"significant":[5],"advancements":[6],"and":[7,14,53,72,78,151,178,195],"garnered":[8],"considerable":[9],"attention":[10,174],"from":[11],"both":[12],"academia":[13],"industry.":[15],"With":[16],"the":[17,23,30,38,64,83,117,127,130,139,144,148,162,167,172,183,189,205,208],"rapid":[18],"development":[19],"of":[20,26,40,119,129,147,166,191,207],"wireless":[21],"technologies,":[22],"vast":[24],"amounts":[25],"data":[27,62,112],"generated":[28],"at":[29,82],"network":[31],"edge":[32,84],"present":[33],"an":[34,95,153],"unprecedented":[35],"opportunity":[36],"for":[37,69],"application":[39],"Network.":[42],"However,":[43,114],"due":[44,115],"to":[45,59,63,103,116,159],"constraints":[46],"such":[47],"as":[48,87],"limited":[49],"bandwidth,":[50],"privacy":[51],"concerns,":[52],"legal":[54],"challenges,":[55],"it":[56],"is":[57,132],"impractical":[58],"transmit":[60],"all":[61],"cloud":[65],"or":[66],"central":[67],"servers":[68],"analysis,":[70],"training,":[71],"processing.":[73],"As":[74],"a":[75,88],"result,":[76],"deploying":[77],"training":[79,109],"emerged":[86],"promising":[89],"alternative":[90],"solution.":[91],"Federated":[92],"learning":[93,98],"(FL),":[94],"emerging":[96],"distributed":[97],"paradigm,":[99],"offers":[100],"potential":[101],"solutions":[102],"this":[104,135],"challenge":[105],"by":[106,142],"enabling":[107],"model":[108,131,197],"while":[110],"preserving":[111],"privacy.":[113],"reliance":[118],"traditional":[120],"on":[123,201],"fixed":[124],"input":[125,145],"formats,":[126],"flexibility":[128,141],"limited.":[133],"In":[134],"paper,":[136],"we":[137,170],"enhance":[138],"model\u2019s":[140],"altering":[143],"format":[146],"introducing":[152],"Adaptive":[154],"Weighted":[155],"Loss.":[157],"Then,":[158],"further":[160],"improve":[161],"feature":[163],"extraction":[164],"capability":[165],"Network,":[169],"incorporate":[171],"CBAM":[173],"module.":[175],"Theoretical":[176],"analysis":[177],"experimental":[179],"results":[180,200],"demonstrate":[181],"that":[182],"improved":[184],"significantly":[187],"enhances":[188],"accuracy":[190],"image":[192],"classification":[193],"tasks":[194],"accelerates":[196],"convergence.":[198],"Experimental":[199],"public":[202],"datasets":[203],"show":[204],"effectiveness":[206],"proposed":[209],"framework.":[210]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}