{"id":"https://openalex.org/W4410770316","doi":"https://doi.org/10.1109/cacml64929.2025.11010976","title":"MCANet: A Multi-Scale Class-Related Attention Network for Few-Shot Learning","display_name":"MCANet: A Multi-Scale Class-Related Attention Network for Few-Shot Learning","publication_year":2025,"publication_date":"2025-03-28","ids":{"openalex":"https://openalex.org/W4410770316","doi":"https://doi.org/10.1109/cacml64929.2025.11010976"},"language":"en","primary_location":{"id":"doi:10.1109/cacml64929.2025.11010976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cacml64929.2025.11010976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 4th Asia Conference on Algorithms, Computing and Machine Learning (CACML)","raw_type":"proceedings-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/A5009400666","display_name":"Yalin Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yalin Duan","raw_affiliation_strings":["Hefei University of Technology,School of Computer Science and Information Engineering,Hefei,China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology,School of Computer Science and Information Engineering,Hefei,China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100638721","display_name":"Lixia Xue","orcid":"https://orcid.org/0000-0002-3515-1226"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lixia Xue","raw_affiliation_strings":["Hefei University of Technology,School of Computer Science and Information Engineering,Hefei,China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology,School of Computer Science and Information Engineering,Hefei,China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101661856","display_name":"Juan Yang","orcid":"https://orcid.org/0000-0002-9004-3244"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Juan Yang","raw_affiliation_strings":["Hefei University of Technology,School of Computer Science and Information Engineering,Hefei,China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology,School of Computer Science and Information Engineering,Hefei,China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079086221","display_name":"Ronggui Wang","orcid":"https://orcid.org/0009-0007-9204-9379"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronggui Wang","raw_affiliation_strings":["Hefei University of Technology,School of Computer Science and Information Engineering,Hefei,China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology,School of Computer Science and Information Engineering,Hefei,China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5009400666"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05949326,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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":0.9853000044822693,"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":0.9853000044822693,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.925000011920929,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.733253002166748},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7052155137062073},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5889851450920105},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5347131490707397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4692271649837494},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.45317134261131287},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07888051867485046},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07825082540512085},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.06056329607963562}],"concepts":[{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.733253002166748},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7052155137062073},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5889851450920105},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5347131490707397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4692271649837494},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.45317134261131287},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07888051867485046},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07825082540512085},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.06056329607963562},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","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},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cacml64929.2025.11010976","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cacml64929.2025.11010976","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 4th Asia Conference on Algorithms, Computing and Machine Learning (CACML)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2138011018","https://openalex.org/W2194775991","https://openalex.org/W2618530766","https://openalex.org/W2752782242","https://openalex.org/W2962799101","https://openalex.org/W2963943197","https://openalex.org/W2964105864","https://openalex.org/W2979689312","https://openalex.org/W3035654071","https://openalex.org/W3097975205","https://openalex.org/W4205245344","https://openalex.org/W4402727051","https://openalex.org/W6736057607","https://openalex.org/W6748284727","https://openalex.org/W6751281049","https://openalex.org/W6752940074","https://openalex.org/W6779702771","https://openalex.org/W6782831966","https://openalex.org/W6783596713","https://openalex.org/W6790291204"],"related_works":["https://openalex.org/W2497720472","https://openalex.org/W4292659306","https://openalex.org/W3044321615","https://openalex.org/W2806221744","https://openalex.org/W2326937258","https://openalex.org/W394267150","https://openalex.org/W2773965352","https://openalex.org/W4294892107","https://openalex.org/W2357748469","https://openalex.org/W2392917037"],"abstract_inverted_index":{"Among":[0],"various":[1,134],"few-shot":[2,64,196],"learning":[3,6],"methods,":[4],"metric":[5],"approaches":[7],"based":[8],"on":[9,182],"local":[10,111,142],"feature":[11,77],"representation":[12],"of":[13,21,41,47,110,140,170],"images":[14,104],"have":[15],"achieved":[16],"remarkable":[17],"results.":[18],"However,":[19],"most":[20],"these":[22,52],"methods":[23],"coarsely":[24],"compare":[25],"support":[26,160],"sets":[27,30,109],"and":[28,44,92,159,174,178],"query":[29,158],"at":[31,113,133],"a":[32,57,75,82],"single":[33],"scale,":[34],"failing":[35],"to":[36,67,85,122,149],"consider":[37],"the":[38,45,138,163,190],"contextual":[39,147],"information":[40,121,148],"image":[42,87],"data":[43,119],"diversity":[46],"multi-scale":[48,76],"information.":[49,102],"To":[50],"address":[51],"issues,":[53],"this":[54],"paper":[55],"proposes":[56],"novel":[58],"Multi-scale":[59],"Class-related":[60],"Attention":[61],"Network":[62],"for":[63,126,156,195],"learning,":[65],"referred":[66],"as":[68,108],"MCANet.":[69],"In":[70],"MCANet,":[71],"we":[72,117,145],"first":[73],"construct":[74],"extraction":[78],"module":[79],"that":[80,189],"adopts":[81],"bottom-up":[83],"architecture":[84],"capture":[86],"features":[88,112,125],"from":[89],"multiple":[90],"scales":[91,135,155],"levels,":[93],"thereby":[94],"combining":[95],"high-level":[96],"semantic":[97],"representations":[98],"with":[99],"low-level":[100],"visual":[101],"The":[103],"are":[105],"then":[106],"represented":[107],"different":[114,154],"scales.":[115],"Next,":[116],"utilize":[118],"co-occurrence":[120],"select":[123],"class-related":[124],"each":[127],"category,":[128],"highlighting":[129],"semantically":[130],"dominant":[131],"objects":[132],"while":[136],"reducing":[137],"influence":[139],"irrelevant":[141],"features.":[143],"Finally,":[144],"integrate":[146],"fuse":[150],"similarity":[151],"measures":[152],"across":[153],"comparing":[157],"sets.":[161],"On":[162],"miniImageNet":[164],"dataset,":[165],"our":[166],"MCANet":[167],"achieves":[168],"accuracies":[169],"71.08%":[171],"(5-way":[172,176],"1-shot)":[173],"83.34%":[175],"5-shot),":[177],"demonstrates":[179],"competitive":[180],"performance":[181],"other":[183],"popular":[184],"benchmarks.":[185],"Experimental":[186],"results":[187],"indicate":[188],"proposed":[191],"method":[192],"is":[193],"effective":[194],"learning.":[197]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
