{"id":"https://openalex.org/W3135674174","doi":"https://doi.org/10.1109/lsp.2021.3061978","title":"Multi-Dimensional Edge Features Graph Neural Network on Few-Shot Image Classification","display_name":"Multi-Dimensional Edge Features Graph Neural Network on Few-Shot Image Classification","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3135674174","doi":"https://doi.org/10.1109/lsp.2021.3061978","mag":"3135674174"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2021.3061978","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3061978","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},"type":"article","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/A5102741305","display_name":"Chao Xiong","orcid":"https://orcid.org/0000-0003-1325-4192"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Xiong","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0003-1325-4192","affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002423609","display_name":"Li Wen","orcid":"https://orcid.org/0000-0002-1498-3103"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Li","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083093046","display_name":"Yun Liu","orcid":"https://orcid.org/0000-0002-9567-5531"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yun Liu","raw_affiliation_strings":["College of Artifical Intelligence, Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-9567-5531","affiliations":[{"raw_affiliation_string":"College of Artifical Intelligence, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100376899","display_name":"Minghui Wang","orcid":"https://orcid.org/0000-0002-1594-136X"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghui Wang","raw_affiliation_strings":["College of Computer Science, Sichuan University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.7302,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.91533449,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"28","issue":null,"first_page":"573","last_page":"577"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T12676","display_name":"Machine Learning and ELM","score":0.996999979019165,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9954000115394592,"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/computer-science","display_name":"Computer science","score":0.7180348038673401},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6551737785339355},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.59852534532547},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5876001715660095},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5713022947311401},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5415080785751343},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.47240012884140015},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45674601197242737},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.42887192964553833},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.29882699251174927},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.08089599013328552}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7180348038673401},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6551737785339355},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.59852534532547},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5876001715660095},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5713022947311401},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5415080785751343},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.47240012884140015},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45674601197242737},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.42887192964553833},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29882699251174927},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.08089599013328552},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2021.3061978","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2021.3061978","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8309642732","display_name":null,"funder_award_id":"SWU119044","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320323172","display_name":"Natural Science Foundation of Chongqing","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W2558748708","https://openalex.org/W2601450892","https://openalex.org/W2604763608","https://openalex.org/W2606780347","https://openalex.org/W2753160622","https://openalex.org/W2786928087","https://openalex.org/W2787705367","https://openalex.org/W2798355657","https://openalex.org/W2899771611","https://openalex.org/W2943605315","https://openalex.org/W2946584829","https://openalex.org/W2950697450","https://openalex.org/W2950763986","https://openalex.org/W2962799101","https://openalex.org/W2962987395","https://openalex.org/W2963070905","https://openalex.org/W2963323244","https://openalex.org/W2963341924","https://openalex.org/W2963858333","https://openalex.org/W2964105864","https://openalex.org/W2964112702","https://openalex.org/W2964206659","https://openalex.org/W2982806777","https://openalex.org/W2995801068","https://openalex.org/W3034251792","https://openalex.org/W3034637015","https://openalex.org/W3035492231","https://openalex.org/W3036587561","https://openalex.org/W3091905774","https://openalex.org/W3124566001","https://openalex.org/W4285723986","https://openalex.org/W4293412117","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6736685754","https://openalex.org/W6743661861","https://openalex.org/W6745537798","https://openalex.org/W6746260573","https://openalex.org/W6747959232","https://openalex.org/W6752232076","https://openalex.org/W6753311412","https://openalex.org/W6756040250","https://openalex.org/W6763315676","https://openalex.org/W6783596713"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W2086519370","https://openalex.org/W2028665553","https://openalex.org/W2087343574","https://openalex.org/W2535915176","https://openalex.org/W2105860728","https://openalex.org/W4287657826"],"abstract_inverted_index":{"Few-shot":[0],"image":[1,132],"classification":[2,32,133],"with":[3,120,136,148],"graph":[4,46,57],"neural":[5,47,58,63],"network":[6,48,59,64,113],"(GNN)":[7],"is":[8],"a":[9,44,94,104],"hot":[10],"topic":[11],"in":[12,82,111],"recent":[13],"years.":[14],"Most":[15],"GNN-based":[16,70],"approaches":[17],"have":[18],"achieved":[19],"promising":[20],"performance.":[21],"These":[22],"methods":[23],"utilize":[24,73],"node":[25,87],"features":[26,52,76,102],"or":[27],"one-dimensional":[28],"edge":[29,35,51,75,80,89,101,106,122],"feature":[30],"for":[31,65],"ignoring":[33],"rich":[34],"featues":[36],"between":[37],"nodes.":[38],"In":[39],"this":[40],"letter,":[41],"we":[42,72,92,144],"propose":[43],"novel":[45],"exploiting":[49],"multi-dimensional":[50,74],"(MDE-GNN)":[53],"based":[54],"on":[55],"edge-labeling":[56],"(EGNN)":[60],"and":[61,88,139],"transductive":[62],"few-shot":[66,131,141],"learning.":[67],"Unlike":[68],"previous":[69,137],"approaches,":[71,143],"information":[77],"to":[78,129],"construct":[79],"matrices":[81],"graph.":[83],"After":[84],"layers":[85],"of":[86],"feautres":[90],"updating,":[91],"generate":[93],"similarity":[95,123],"score":[96],"matrix":[97],"by":[98,117],"the":[99],"mulit-dimensional":[100],"through":[103],"well-designed":[105],"aggregation":[107],"module.":[108],"The":[109],"parameters":[110],"our":[112,127],"are":[114],"iteratively":[115],"learnt":[116],"episode":[118],"training":[119],"an":[121],"loss.":[124],"We":[125],"apply":[126],"model":[128],"supervised":[130],"tasks.":[134],"Compared":[135],"GNNs":[138],"other":[140],"learning":[142],"achieve":[145],"state-of-the-art":[146],"performance":[147],"two":[149],"benchmark":[150],"datasets.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":11},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2025-10-10T00:00:00"}
