{"id":"https://openalex.org/W7125964173","doi":"https://doi.org/10.1109/tip.2026.3657170","title":"A Few-Shot Class Incremental Learning Method Using Graph Neural Networks","display_name":"A Few-Shot Class Incremental Learning Method Using Graph Neural Networks","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7125964173","doi":"https://doi.org/10.1109/tip.2026.3657170","pmid":"https://pubmed.ncbi.nlm.nih.gov/41605152"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2026.3657170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3657170","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/A5069689957","display_name":"Yuqian Ma","orcid":"https://orcid.org/0000-0003-0162-2410"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuqian Ma","raw_affiliation_strings":["School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056810715","display_name":"Youfa Liu","orcid":"https://orcid.org/0000-0002-3540-5775"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youfa Liu","raw_affiliation_strings":["School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-3540-5775","affiliations":[{"raw_affiliation_string":"School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122853580","display_name":"Bo Du","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Du","raw_affiliation_strings":["School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-0059-8458","affiliations":[{"raw_affiliation_string":"School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":12.1051,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.96373833,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"35","issue":null,"first_page":"1337","last_page":"1349"},"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":0.7161999940872192,"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":0.7161999940872192,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.1589999943971634,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.07909999787807465,"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/scalability","display_name":"Scalability","score":0.5198000073432922},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4814999997615814},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.42170000076293945},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.4140999913215637},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.400299996137619},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.38359999656677246},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.3806000053882599},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.37779998779296875}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7343999743461609},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6033999919891357},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5198000073432922},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5180000066757202},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.48669999837875366},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4814999997615814},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.42170000076293945},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.4140999913215637},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.400299996137619},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.38359999656677246},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.37779998779296875},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.31150001287460327},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.29980000853538513},{"id":"https://openalex.org/C136643341","wikidata":"https://www.wikidata.org/wiki/Q1361526","display_name":"Reachability","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2646999955177307},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.25529998540878296}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2026.3657170","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2026.3657170","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:41605152","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41605152","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/G1836220556","display_name":null,"funder_award_id":"62225113","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3159897870","display_name":null,"funder_award_id":"62576257","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5602205313","display_name":null,"funder_award_id":"2023YFC2705702","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8400922664","display_name":null,"funder_award_id":"2023YFC2705700","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8813169933","display_name":null,"funder_award_id":"2024YFF1207300","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W2117539524","https://openalex.org/W2808409763","https://openalex.org/W2914482044","https://openalex.org/W2961553857","https://openalex.org/W2966228599","https://openalex.org/W2974686944","https://openalex.org/W2976669726","https://openalex.org/W3085084733","https://openalex.org/W3096719817","https://openalex.org/W3152893301","https://openalex.org/W3175771944","https://openalex.org/W3177494822","https://openalex.org/W3204196975","https://openalex.org/W3212386989","https://openalex.org/W4220848104","https://openalex.org/W4226134030","https://openalex.org/W4283802263","https://openalex.org/W4289656036","https://openalex.org/W4292973282","https://openalex.org/W4312327301","https://openalex.org/W4313005250","https://openalex.org/W4313143666","https://openalex.org/W4320731432","https://openalex.org/W4360993849","https://openalex.org/W4376115475","https://openalex.org/W4385196562","https://openalex.org/W4386057810","https://openalex.org/W4389610214","https://openalex.org/W4390189747","https://openalex.org/W4390344720","https://openalex.org/W4390416375","https://openalex.org/W4390659157","https://openalex.org/W4390874440","https://openalex.org/W4390973074","https://openalex.org/W4392121983","https://openalex.org/W4392902760","https://openalex.org/W4394592973","https://openalex.org/W4400315380","https://openalex.org/W4400905561","https://openalex.org/W4402352168","https://openalex.org/W4402716128","https://openalex.org/W4402754181","https://openalex.org/W4403939032","https://openalex.org/W4406354592","https://openalex.org/W4406729765","https://openalex.org/W4406813556","https://openalex.org/W4407363198","https://openalex.org/W4407953171","https://openalex.org/W4408345596","https://openalex.org/W4408755510","https://openalex.org/W4412030570"],"related_works":[],"abstract_inverted_index":{"Few-shot":[0],"class":[1],"incremental":[2,155],"learning":[3,134],"(FSCIL)":[4],"aims":[5],"to":[6,50,72,87,103,123,140,160],"continuously":[7],"learn":[8],"new":[9],"classes":[10],"from":[11],"limited":[12],"training":[13,89],"samples":[14],"while":[15],"retaining":[16],"previously":[17],"acquired":[18],"knowledge.":[19],"Existing":[20],"approaches":[21],"are":[22],"not":[23],"fully":[24],"capable":[25],"of":[26],"balancing":[27],"stability":[28,158],"and":[29,56,95,129,144,157,178],"plasticity":[30],"in":[31],"dynamic":[32],"scenarios.":[33],"To":[34],"overcome":[35],"this":[36],"limitation,":[37],"we":[38],"introduce":[39],"a":[40,67,79,113,176],"novel":[41],"FSCIL":[42,166],"framework":[43,61],"that":[44],"leverages":[45],"graph":[46,121],"neural":[47],"networks":[48],"(GNNs)":[49],"model":[51,124],"interdependencies":[52],"between":[53,127],"different":[54],"categories":[55],"enhance":[57],"cross-modal":[58],"alignment.":[59],"Our":[60],"incorporates":[62],"three":[63],"key":[64],"components:":[65],"1)":[66],"Graph":[68,81,100],"Isomorphism":[69],"Network":[70,82],"(GIN)":[71],"propagate":[73],"contextual":[74],"relationships":[75],"among":[76],"prompts;":[77],"2)":[78],"Hamiltonian":[80],"with":[83,112,135,172],"Energy":[84],"Conservation":[85],"(HGN-EC)":[86],"stabilize":[88],"dynamics":[90],"via":[91],"energy":[92],"conservation":[93],"constraints;":[94],"3)":[96],"an":[97],"Adversarially":[98],"Constrained":[99],"Autoencoder":[101],"(ACGA)":[102],"enforce":[104],"latent":[105],"space":[106],"consistency.":[107],"By":[108],"integrating":[109],"these":[110],"components":[111],"parameter-efficient":[114],"CLIP":[115],"backbone,":[116],"our":[117],"method":[118],"dynamically":[119],"adapts":[120],"structures":[122],"semantic":[125],"correlations":[126],"textual":[128],"visual":[130],"modalities.":[131],"Additionally,":[132],"contrastive":[133],"energy-based":[136],"regularization":[137],"is":[138,182],"employed":[139],"mitigate":[141],"catastrophic":[142],"forgetting":[143],"improve":[145],"generalization.":[146],"Comprehensive":[147],"experiments":[148],"on":[149],"benchmark":[150],"datasets":[151],"validate":[152],"the":[153],"framework's":[154],"accuracy":[156],"compared":[159],"state-of-the-art":[161],"baselines.":[162],"This":[163],"work":[164],"advances":[165],"by":[167],"unifying":[168],"graph-based":[169],"relational":[170],"reasoning":[171],"physics-inspired":[173],"optimization,":[174],"offering":[175],"scalable":[177],"interpretable":[179],"framework.":[180],"Code":[181],"available":[183],"at:":[184],"https://github.com/aries-yqian/ACHG-CLIP.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-02-09T05:59:30.833894","created_date":"2026-01-29T00:00:00"}
