{"id":"https://openalex.org/W4214842573","doi":"https://doi.org/10.1109/tip.2022.3154938","title":"Sample-Centric Feature Generation for Semi-Supervised Few-Shot Learning","display_name":"Sample-Centric Feature Generation for Semi-Supervised Few-Shot Learning","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4214842573","doi":"https://doi.org/10.1109/tip.2022.3154938","pmid":"https://pubmed.ncbi.nlm.nih.gov/35245196"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2022.3154938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3154938","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/A5100335202","display_name":"Bo Zhang","orcid":"https://orcid.org/0000-0001-8052-782X"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Zhang","raw_affiliation_strings":["School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-8052-782X","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000892367","display_name":"Hancheng Ye","orcid":"https://orcid.org/0000-0002-6272-2792"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hancheng Ye","raw_affiliation_strings":["School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-6272-2792","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003400275","display_name":"Gang Yu","orcid":"https://orcid.org/0000-0001-5570-2710"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gang Yu","raw_affiliation_strings":["Tencent GY-Laboratory, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5570-2710","affiliations":[{"raw_affiliation_string":"Tencent GY-Laboratory, Shanghai, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059575276","display_name":"Bin Wang","orcid":"https://orcid.org/0000-0003-4748-6426"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wang","raw_affiliation_strings":["School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-4748-6426","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075742545","display_name":"Yike Wu","orcid":"https://orcid.org/0000-0001-7384-8836"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yike Wu","raw_affiliation_strings":["School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102013595","display_name":"Jiayuan Fan","orcid":"https://orcid.org/0000-0001-7494-0255"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayuan Fan","raw_affiliation_strings":["Academy for Engineering and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-7494-0255","affiliations":[{"raw_affiliation_string":"Academy for Engineering and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021220108","display_name":"Tao Chen","orcid":"https://orcid.org/0000-0002-0779-9818"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Chen","raw_affiliation_strings":["School of Information Science and Technology, Fudan University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-0779-9818","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0145,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.92012053,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":"31","issue":null,"first_page":"2309","last_page":"2320"},"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":0.9991999864578247,"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":0.9991999864578247,"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":0.9763000011444092,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9289000034332275,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7628648281097412},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7087750434875488},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.680233359336853},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.638064980506897},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5980531573295593},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.5832207202911377},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5195222496986389},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4757901430130005},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.47534844279289246},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.4410228431224823},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4313364624977112},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3803997039794922},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34976065158843994},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22403749823570251},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.19446128606796265}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7628648281097412},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7087750434875488},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.680233359336853},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.638064980506897},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5980531573295593},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.5832207202911377},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5195222496986389},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4757901430130005},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.47534844279289246},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.4410228431224823},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4313364624977112},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3803997039794922},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34976065158843994},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22403749823570251},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.19446128606796265},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2022.3154938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2022.3154938","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:35245196","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35245196","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":[{"id":"https://metadata.un.org/sdg/10","score":0.7200000286102295,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G3977413633","display_name":"\u5b50\u7c7b\u611f\u77e5\u6df1\u5ea6\u5b66\u4e60\u7406\u8bba\u53ca\u5176\u5e94\u7528\u7814\u7a76","funder_award_id":"62071127","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7626924423","display_name":null,"funder_award_id":"62101137","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8387295191","display_name":null,"funder_award_id":"2021SHZDZX0103","funder_id":"https://openalex.org/F4320327832","funder_display_name":"Shantou Science and Technology Project"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327832","display_name":"Shantou Science and Technology Project","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1797268635","https://openalex.org/W1903029394","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2560023338","https://openalex.org/W2724492314","https://openalex.org/W2752782242","https://openalex.org/W2798836702","https://openalex.org/W2894906112","https://openalex.org/W2904008038","https://openalex.org/W2909383239","https://openalex.org/W2957105406","https://openalex.org/W2963070905","https://openalex.org/W2963078860","https://openalex.org/W2963350370","https://openalex.org/W2963351448","https://openalex.org/W2963446712","https://openalex.org/W2963845150","https://openalex.org/W2963943197","https://openalex.org/W2964105864","https://openalex.org/W2981707695","https://openalex.org/W2983156430","https://openalex.org/W2984618279","https://openalex.org/W2988501586","https://openalex.org/W2994633389","https://openalex.org/W2995360785","https://openalex.org/W2997820257","https://openalex.org/W2998468066","https://openalex.org/W3034453888","https://openalex.org/W3035370595","https://openalex.org/W3035531117","https://openalex.org/W3093163175","https://openalex.org/W3096805028","https://openalex.org/W3099486271","https://openalex.org/W3099554308","https://openalex.org/W3107322323","https://openalex.org/W3107763055","https://openalex.org/W3108878460","https://openalex.org/W3108975329","https://openalex.org/W3109083691","https://openalex.org/W3110214837","https://openalex.org/W3118608800","https://openalex.org/W3128992469","https://openalex.org/W3176049064","https://openalex.org/W3202483439","https://openalex.org/W3205249428","https://openalex.org/W3206402863","https://openalex.org/W4205826960","https://openalex.org/W6638319203","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6745674251","https://openalex.org/W6746260573","https://openalex.org/W6748284727","https://openalex.org/W6750523955","https://openalex.org/W6751281049","https://openalex.org/W6752232076","https://openalex.org/W6752940074","https://openalex.org/W6753311412","https://openalex.org/W6754654810","https://openalex.org/W6755766585","https://openalex.org/W6758126075","https://openalex.org/W6760842081","https://openalex.org/W6762818971","https://openalex.org/W6763752302","https://openalex.org/W6767252667","https://openalex.org/W6768230505","https://openalex.org/W6771260093","https://openalex.org/W6784403933","https://openalex.org/W6784522328","https://openalex.org/W6784924269","https://openalex.org/W6787972765","https://openalex.org/W6788840927","https://openalex.org/W6800539454"],"related_works":["https://openalex.org/W3006513224","https://openalex.org/W2046456988","https://openalex.org/W2357409937","https://openalex.org/W2510582230","https://openalex.org/W2978674666","https://openalex.org/W2074430941","https://openalex.org/W2113096305","https://openalex.org/W1977636359","https://openalex.org/W2772305933","https://openalex.org/W2580722822"],"abstract_inverted_index":{"Semi-supervised":[0],"few-shot":[1,30,93,98,190],"learning":[2],"aims":[3],"to":[4,24,107,121,143,148,165],"improve":[5],"the":[6,26,29,51,56,72,76,97,111,131,136,140,149,153,167,178,181],"model":[7,25,173],"generalization":[8],"ability":[9],"by":[10,37,55],"means":[11],"of":[12,169,180],"both":[13],"limited":[14],"labeled":[15,31,99],"data":[16,32,58,74],"and":[17,33,75,146,189],"widely-available":[18],"unlabeled":[19,35,113],"data.":[20,79],"Previous":[21],"works":[22],"attempt":[23],"relations":[27],"between":[28,71],"extra":[34],"data,":[36],"performing":[38],"a":[39,67,85,116,158],"label":[40],"propagation":[41],"or":[42],"pseudo-labeling":[43],"process":[44],"using":[45],"an":[46],"episodic":[47],"training":[48],"strategy.":[49],"However,":[50],"feature":[52,87,133,155,183],"distribution":[53,69],"represented":[54],"pseudo-labeled":[57,73,128,150],"itself":[59],"is":[60,119,163],"coarse-grained,":[61],"meaning":[62],"that":[63],"there":[64],"might":[65],"be":[66,144],"large":[68],"gap":[70],"real":[77],"query":[78],"To":[80],"this":[81],"end,":[82],"we":[83],"propose":[84],"sample-centric":[86,137],"generation":[88,138,184],"(SFG)":[89],"approach":[90,185],"for":[91,110],"semi-supervised":[92,117],"image":[94,191],"classification.":[95],"Specifically,":[96],"samples":[100],"from":[101],"different":[102],"classes":[103],"are":[104],"initially":[105],"trained":[106],"predict":[108],"pseudo-labels":[109],"potential":[112],"samples.":[114],"Next,":[115],"meta-generator":[118],"utilized":[120],"produce":[122],"derivative":[123],"features":[124,142],"centering":[125],"around":[126],"each":[127],"sample,":[129,151],"enriching":[130],"intra-class":[132],"diversity.":[134],"Meanwhile,":[135],"constrains":[139],"generated":[141,170],"compact":[145],"close":[147],"ensuring":[152],"inter-class":[154],"discriminability.":[156],"Further,":[157],"reliability":[159],"assessment":[160],"(RA)":[161],"metric":[162],"developed":[164],"weaken":[166],"influence":[168],"outliers":[171],"on":[172,186],"learning.":[174],"Extensive":[175],"experiments":[176],"validate":[177],"effectiveness":[179],"proposed":[182],"challenging":[187],"one-":[188],"classification":[192],"benchmarks.":[193]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}