{"id":"https://openalex.org/W7136170472","doi":"https://doi.org/10.1109/tip.2026.3672375","title":"Heterogeneous Federated Dynamic Graph HyperNetwork for Image Classification","display_name":"Heterogeneous Federated Dynamic Graph HyperNetwork for Image Classification","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7136170472","doi":"https://doi.org/10.1109/tip.2026.3672375","pmid":"https://pubmed.ncbi.nlm.nih.gov/41838497"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3672375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3672375","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5129458326","display_name":"Liu Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liu Yang","raw_affiliation_strings":["School of Artificial Intelligence, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-8555-5387","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129406438","display_name":"Kegen Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kegen Chen","raw_affiliation_strings":["State Key Laboratory of Synthetic Biology, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0009-0008-0424-7496","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetic Biology, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129525928","display_name":"Qilong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qilong Wang","raw_affiliation_strings":["State Key Laboratory of Synthetic Biology, Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetic Biology, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129456189","display_name":"Zhengyi Xu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210087373","display_name":"Meizu (China)","ror":"https://ror.org/0067g4302","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210087373"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyi Xu","raw_affiliation_strings":["Meituan, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan, Beijing, China","institution_ids":["https://openalex.org/I4210087373"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108507563","display_name":"Shenyan Gu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210128910","display_name":"Group Sense (China)","ror":"https://ror.org/036wd5777","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210128910"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiqiao Gu","raw_affiliation_strings":["SenseTime Research, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SenseTime Research, Beijing, China","institution_ids":["https://openalex.org/I4210128910"]}]},{"author_position":"last","author":{"id":null,"display_name":"Qinghua Hu","orcid":"https://orcid.org/0000-0001-7765-8095"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinghua Hu","raw_affiliation_strings":["School of Artificial Intelligence, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-7765-8095","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"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":0.26594707,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":null,"first_page":"3009","last_page":"3022"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.8172000050544739,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.8172000050544739,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.034699998795986176,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.01940000057220459,"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/contextual-image-classification","display_name":"Contextual image classification","score":0.5424000024795532},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46389999985694885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4551999866962433},{"id":"https://openalex.org/keywords/graph-theory","display_name":"Graph theory","score":0.3840999901294708},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.37929999828338623},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.3553999960422516},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.3529999852180481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6980999708175659},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5424000024795532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4690999984741211},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46389999985694885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4551999866962433},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.3840999901294708},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.37929999828338623},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3553999960422516},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.3529999852180481},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3522999882698059},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3472999930381775},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34150001406669617},{"id":"https://openalex.org/C34872919","wikidata":"https://www.wikidata.org/wiki/Q7092302","display_name":"One-class classification","level":3,"score":0.3361000120639801},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.30880001187324524},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28450000286102295},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.28380000591278076},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C13460635","wikidata":"https://www.wikidata.org/wiki/Q85753676","display_name":"Classification scheme","level":2,"score":0.27549999952316284},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.25999999046325684},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2515999972820282}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3672375","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3672375","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:41838497","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41838497","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1646227055","display_name":null,"funder_award_id":"22527901","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2119491282","display_name":null,"funder_award_id":"JYB2025XDXM503","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5070492027","display_name":null,"funder_award_id":"U23B2049","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6521765114","display_name":null,"funder_award_id":"62476194","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7149946468","display_name":null,"funder_award_id":"62476194, U23B2049","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Federated":[0,66],"learning":[1],"(FL)":[2],"enables":[3],"privacy-preserving":[4],"collaboration":[5,92],"among":[6],"distributed":[7],"clients,":[8,137],"but":[9],"practical":[10],"deployments":[11],"often":[12],"face":[13],"heterogeneous":[14,102,167],"models":[15,72],"and":[16,23,39,50,75,166,174],"non-IID":[17],"data,":[18],"leading":[19],"to":[20,88,124,141,163],"degraded":[21],"communication":[22],"personalization.":[24],"In":[25],"addition,":[26],"real-world":[27,177],"FL":[28,168],"systems":[29],"frequently":[30],"encounter":[31],"newly":[32,125],"joined":[33,126],"clients":[34,41],"that":[35,42,70,157],"require":[36],"rapid":[37],"adaptation":[38,123],"abnormal":[40,136],"may":[43],"upload":[44],"corrupted":[45],"updates,":[46],"further":[47],"exacerbating":[48],"instability":[49],"hindering":[51],"global":[52],"convergence.":[53],"To":[54],"address":[55],"these":[56],"challenges":[57],"in":[58,176],"image":[59],"classification,":[60],"we":[61],"propose":[62],"HFedDGHN,":[63],"a":[64,80,90,95],"Heterogeneous":[65],"Dynamic":[67],"Graph":[68],"HyperNetwork":[69],"jointly":[71],"inter-client":[73],"relations":[74],"personalized":[76,165],"parameter":[77],"generation.":[78],"Specifically,":[79],"graph":[81,131,149],"structure":[82],"learner":[83],"adaptively":[84],"captures":[85],"client":[86],"correlations":[87],"construct":[89],"dynamic":[91,130],"graph,":[93],"while":[94,170],"graph-convolutional":[96],"hypernetwork":[97],"generates":[98],"model":[99],"parameters":[100],"for":[101],"architectures,":[103],"enabling":[104],"implicit":[105],"knowledge":[106],"transfer":[107],"without":[108],"sharing":[109],"local":[110],"data":[111],"or":[112],"weights.":[113],"Moreover,":[114],"the":[115,129],"framework":[116],"naturally":[117,171],"supports":[118],"meta-learning-based":[119],"generalization,":[120],"allowing":[121],"efficient":[122],"clients.":[127],"Furthermore,":[128],"enhances":[132],"robustness":[133,173],"by":[134],"isolating":[135],"as":[138],"they":[139],"tend":[140],"be":[142],"excluded":[143],"from":[144],"most":[145],"neighborhoods":[146],"during":[147],"adaptive":[148],"construction.":[150],"Extensive":[151],"experiments":[152],"across":[153],"multiple":[154],"benchmarks":[155],"demonstrate":[156],"HFedDGHN":[158],"achieves":[159],"superior":[160],"accuracy":[161],"compared":[162],"state-of-the-art":[164],"methods,":[169],"improving":[172],"scalability":[175],"deployments.":[178]},"counts_by_year":[],"updated_date":"2026-03-24T05:59:24.953642","created_date":"2026-03-17T00:00:00"}
