{"id":"https://openalex.org/W4407127895","doi":"https://doi.org/10.1109/access.2025.3538610","title":"Cluster-HGNN: Deep Local Features Clustering for Few-Shot Image Classification With Hybrid Graph Neural Networks","display_name":"Cluster-HGNN: Deep Local Features Clustering for Few-Shot Image Classification With Hybrid Graph Neural Networks","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4407127895","doi":"https://doi.org/10.1109/access.2025.3538610"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3538610","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3538610","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3538610","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Hongxuan Wu","orcid":"https://orcid.org/0009-0006-0361-8211"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxuan Wu","raw_affiliation_strings":["School of Computer and Electronic Information, Nanjing Normal University, Nanjing, China"],"raw_orcid":"https://orcid.org/0009-0006-0361-8211","affiliations":[{"raw_affiliation_string":"School of Computer and Electronic Information, Nanjing Normal University, Nanjing, China","institution_ids":["https://openalex.org/I152031979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076978644","display_name":"Like Xin","orcid":"https://orcid.org/0000-0002-7516-4355"},"institutions":[{"id":"https://openalex.org/I152031979","display_name":"Nanjing Normal University","ror":"https://ror.org/036trcv74","country_code":"CN","type":"education","lineage":["https://openalex.org/I152031979"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Like Xin","raw_affiliation_strings":["School of Mathematical Sciences, Nanjing Normal University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-7516-4355","affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Nanjing Normal University, Nanjing, China","institution_ids":["https://openalex.org/I152031979"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I152031979"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.396,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82170398,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"13","issue":null,"first_page":"30965","last_page":"30975"},"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":0.9934999942779541,"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":0.9934999942779541,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9782999753952026,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9656000137329102,"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/cluster-analysis","display_name":"Cluster analysis","score":0.6754618883132935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6689974665641785},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6529589891433716},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6452751159667969},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.5409894585609436},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4741223156452179},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4590983986854553},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.4329730272293091},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34900906682014465}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6754618883132935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6689974665641785},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6529589891433716},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6452751159667969},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.5409894585609436},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4741223156452179},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4590983986854553},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.4329730272293091},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34900906682014465},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3538610","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3538610","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2c8f9b3b38ce49a490ba48fdc9747b65","is_oa":true,"landing_page_url":"https://doaj.org/article/2c8f9b3b38ce49a490ba48fdc9747b65","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 30965-30975 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3538610","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3538610","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1642746288","display_name":null,"funder_award_id":"KYCX24_1865","funder_id":"https://openalex.org/F4320334982","funder_display_name":"Basic Research Program of Jiangsu Province"},{"id":"https://openalex.org/G4459702006","display_name":null,"funder_award_id":"62276138","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G714982415","display_name":null,"funder_award_id":"61876087","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"},{"id":"https://openalex.org/F4320334982","display_name":"Basic Research Program of Jiangsu Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1965555277","https://openalex.org/W2115733720","https://openalex.org/W2117539524","https://openalex.org/W2143668817","https://openalex.org/W2194775991","https://openalex.org/W2604559389","https://openalex.org/W2618530766","https://openalex.org/W2741700122","https://openalex.org/W2904218366","https://openalex.org/W2943605315","https://openalex.org/W2944851425","https://openalex.org/W2964051675","https://openalex.org/W2964105864","https://openalex.org/W2979689312","https://openalex.org/W2979750740","https://openalex.org/W2981787211","https://openalex.org/W2983156430","https://openalex.org/W2990045899","https://openalex.org/W2998528009","https://openalex.org/W3012255272","https://openalex.org/W3034296706","https://openalex.org/W3034637015","https://openalex.org/W3034942609","https://openalex.org/W3034974675","https://openalex.org/W3034985049","https://openalex.org/W3035135368","https://openalex.org/W3035143213","https://openalex.org/W3035492231","https://openalex.org/W3094724482","https://openalex.org/W3096805028","https://openalex.org/W3110608229","https://openalex.org/W3161727935","https://openalex.org/W3174480022","https://openalex.org/W3175609671","https://openalex.org/W3176341011","https://openalex.org/W3197269428","https://openalex.org/W3199180109","https://openalex.org/W4206455827","https://openalex.org/W4225922017","https://openalex.org/W4226038224","https://openalex.org/W4283802263","https://openalex.org/W4287121509","https://openalex.org/W4288073030","https://openalex.org/W4312770623","https://openalex.org/W4385565200","https://openalex.org/W4386065561","https://openalex.org/W4386071574","https://openalex.org/W4390873987","https://openalex.org/W4390970452","https://openalex.org/W4398226150","https://openalex.org/W4402510265","https://openalex.org/W6600609147","https://openalex.org/W6717697761","https://openalex.org/W6720057410","https://openalex.org/W6736057607","https://openalex.org/W6738964360","https://openalex.org/W6748284727","https://openalex.org/W6748555532","https://openalex.org/W6753311412","https://openalex.org/W6754568377","https://openalex.org/W6754929296","https://openalex.org/W6755766585","https://openalex.org/W6755977528","https://openalex.org/W6768314895","https://openalex.org/W6772329248","https://openalex.org/W6774983715","https://openalex.org/W6783596713","https://openalex.org/W6848935878"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2366718574","https://openalex.org/W2359774528","https://openalex.org/W4298312966","https://openalex.org/W2325697621"],"abstract_inverted_index":{"Graph":[0],"neural":[1,67],"networks":[2],"(GNNs)":[3],"have":[4],"shown":[5],"great":[6],"promise":[7],"in":[8,147],"few-shot":[9,70,191],"learning,":[10],"where":[11,149],"they":[12],"typically":[13],"represent":[14],"the":[15,32,38,106,120,131,142,150,156,160,169,174],"entire":[16],"feature":[17,88,93,109,170],"of":[18,84,122,176],"a":[19,22,59,64,86,91,183],"sample":[20],"as":[21,34,111],"node.":[23],"However,":[24],"this":[25,55],"approach":[26],"can":[27],"overlook":[28],"finer":[29],"details":[30],"within":[31],"sample,":[33],"GNNs":[35],"usually":[36],"measure":[37],"distance":[39],"between":[40],"nodes":[41],"to":[42,49,101,129,140,167],"determine":[43],"overall":[44],"differences,":[45],"making":[46],"them":[47],"prone":[48],"background":[50,177],"noise":[51,178],"interference.":[52],"To":[53],"alleviate":[54],"limitation,":[56],"we":[57],"propose":[58],"novel":[60],"framework":[61,80,161],"based":[62],"on":[63,179,189],"hybrid":[65],"graph":[66],"network":[68],"for":[69],"image":[71,192],"classification,":[72],"incorporating":[73],"deep":[74,113],"local":[75,92,114,138],"features":[76,139,152],"clustering":[77,166],"(Cluster-HGNN).":[78],"This":[79],"comprises":[81],"two":[82],"types":[83],"GNNs:":[85],"global":[87,151],"GNN":[89],"and":[90,165,172],"GNN.":[94],"The":[95,134],"former":[96],"applies":[97],"traditional":[98],"label":[99],"propagation":[100],"classify":[102],"query":[103,124],"nodes,":[104],"while":[105],"latter":[107],"treats":[108],"embeddings":[110],"multiple":[112],"features,":[115],"aggregating":[116],"these":[117],"by":[118],"analyzing":[119],"categories":[121],"each":[123],"node\u2019s":[125],"K":[126],"nearest":[127],"neighbours":[128],"infer":[130],"sample\u2019s":[132],"category.":[133],"proposed":[135],"design":[136],"incorporates":[137],"rectify":[141],"final":[143],"classification":[144,180,193],"outcome,":[145],"even":[146],"scenarios":[148],"may":[153],"inaccurately":[154],"assess":[155],"current":[157],"sample.":[158],"Furthermore,":[159],"integrates":[162],"multi-scale":[163],"techniques":[164],"expand":[168],"space":[171],"reduce":[173],"influence":[175],"performance.":[181],"As":[182],"result,":[184],"Cluster-HGNN":[185],"achieves":[186],"state-of-the-art":[187],"results":[188],"standard":[190],"benchmarks.":[194]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
