{"id":"https://openalex.org/W4416183973","doi":"https://doi.org/10.1109/sibgrapi67909.2025.11223411","title":"Curriculum-Based Meta-Pseudo-Labeling on 2D Projections for Active Semi-Supervised Learning","display_name":"Curriculum-Based Meta-Pseudo-Labeling on 2D Projections for Active Semi-Supervised Learning","publication_year":2025,"publication_date":"2025-09-30","ids":{"openalex":"https://openalex.org/W4416183973","doi":"https://doi.org/10.1109/sibgrapi67909.2025.11223411"},"language":null,"primary_location":{"id":"doi:10.1109/sibgrapi67909.2025.11223411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sibgrapi67909.2025.11223411","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 38th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","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/A5012829082","display_name":"David Aparco-Cardenas","orcid":"https://orcid.org/0000-0003-2537-7050"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"David Aparco-Cardenas","raw_affiliation_strings":["Institute of Computing (IC), University of Campinas (UNICAMP),Campinas,Brazil"],"affiliations":[{"raw_affiliation_string":"Institute of Computing (IC), University of Campinas (UNICAMP),Campinas,Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000839360","display_name":"Jancarlo Ferreira Gomes","orcid":"https://orcid.org/0000-0002-2466-7315"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Jancarlo F. Gomes","raw_affiliation_strings":["Institute of Computing (IC), University of Campinas (UNICAMP),Campinas,Brazil"],"affiliations":[{"raw_affiliation_string":"Institute of Computing (IC), University of Campinas (UNICAMP),Campinas,Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015267493","display_name":"Alexandre X. Falc\u00e3o","orcid":"https://orcid.org/0000-0002-2914-5380"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Alexandre X. Falc\u00e3o","raw_affiliation_strings":["Institute of Computing (IC), University of Campinas (UNICAMP),Campinas,Brazil"],"affiliations":[{"raw_affiliation_string":"Institute of Computing (IC), University of Campinas (UNICAMP),Campinas,Brazil","institution_ids":["https://openalex.org/I181391015"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080024357","display_name":"Pedro J. de Rezende","orcid":"https://orcid.org/0000-0002-9529-4253"},"institutions":[{"id":"https://openalex.org/I181391015","display_name":"Universidade Estadual de Campinas (UNICAMP)","ror":"https://ror.org/04wffgt70","country_code":"BR","type":"education","lineage":["https://openalex.org/I181391015"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Pedro J. de Rezende","raw_affiliation_strings":["Institute of Computing (IC), University of Campinas (UNICAMP),Campinas,Brazil"],"affiliations":[{"raw_affiliation_string":"Institute of Computing (IC), University of Campinas (UNICAMP),Campinas,Brazil","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5012829082"],"corresponding_institution_ids":["https://openalex.org/I181391015"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18041559,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.6072999835014343,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.6072999835014343,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.15389999747276306,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.09600000083446503,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6407999992370605},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6053000092506409},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5796999931335449},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.550000011920929},{"id":"https://openalex.org/keywords/oracle","display_name":"Oracle","score":0.4763000011444092},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.47620001435279846},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4438000023365021},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.43470001220703125},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.43140000104904175}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7444000244140625},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7042999863624573},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6407999992370605},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6053000092506409},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5796999931335449},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.550000011920929},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.4763000011444092},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.47620001435279846},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43470001220703125},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.43140000104904175},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41780000925064087},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.40610000491142273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40119999647140503},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.36320000886917114},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.36239999532699585},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3422999978065491},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3206999897956848},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C174576160","wikidata":"https://www.wikidata.org/wiki/Q1183700","display_name":"Deconvolution","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C199579030","wikidata":"https://www.wikidata.org/wiki/Q2851778","display_name":"Automatic image annotation","level":4,"score":0.25780001282691956},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sibgrapi67909.2025.11223411","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sibgrapi67909.2025.11223411","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 38th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3922981914","display_name":null,"funder_award_id":"2023/14427-8,2013/07375-0","funder_id":"https://openalex.org/F4320320997","funder_display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo"},{"id":"https://openalex.org/G6235306638","display_name":null,"funder_award_id":"140930/2021-3,314293/2023-0,442950/2023-3,304711/2023-3","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"}],"funders":[{"id":"https://openalex.org/F4320320997","display_name":"Funda\u00e7\u00e3o de Amparo \u00e0 Pesquisa do Estado de S\u00e3o Paulo","ror":"https://ror.org/02ddkpn78"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1969328404","https://openalex.org/W2398616336","https://openalex.org/W3035682985","https://openalex.org/W3136021864","https://openalex.org/W3174697615","https://openalex.org/W3205626500","https://openalex.org/W4286909227","https://openalex.org/W4367396468","https://openalex.org/W4403535143","https://openalex.org/W4404565662"],"related_works":[],"abstract_inverted_index":{"Semi-supervised":[0],"learning":[1,34,63],"(SSL)":[2],"is":[3,120],"an":[4,137],"effective":[5],"approach":[6],"to":[7,87,122,146,159],"addressing":[8],"the":[9,140],"scarcity":[10],"of":[11,177],"accurately":[12],"labeled":[13,17,27,96,112,178],"data,":[14,179],"leveraging":[15],"both":[16],"and":[18,51,58,84,98,156,185,191],"unlabeled":[19,100],"samples":[20,41],"for":[21,42,62,91,163],"deep":[22,124],"model":[23],"training.":[24],"However,":[25],"limited":[26,175],"data":[28,97],"can":[29],"constrain":[30],"its":[31],"effectiveness.":[32],"Active":[33],"(AL)":[35],"mitigates":[36],"this":[37],"by":[38,188],"selecting":[39],"informative":[40,142],"human":[43],"annotation,":[44],"enhancing":[45],"SSL":[46,52],"performance.":[47],"Most":[48],"state-of-the-art":[49,186],"AL":[50],"methods":[53],"depend":[54],"on":[55,109,167],"pre-trained":[56],"features":[57],"large":[59],"validation":[60],"sets":[61],"representations":[64,162],"in":[65],"classification":[66,93],"tasks.":[67],"We":[68],"introduce":[69],"contrastive":[70,80,107],"active":[71,82],"Deep":[72],"Feature":[73],"Annotation":[74],"(ca-DeepFA),":[75],"a":[76,110,133,147,174],"method":[77,181],"that":[78,151],"integrates":[79],"learning,":[81,83],"curriculum-based":[85],"meta-pseudolabeling":[86],"train":[88],"non-pre-trained":[89],"CNNs":[90],"image":[92,164,171],"with":[94,105,173],"minimal":[95],"abundant":[99],"samples.":[101,143],"The":[102],"process":[103],"begins":[104],"unsupervised":[106],"pre-training":[108],"small":[111],"set.":[113],"At":[114],"regular":[115],"epoch":[116],"intervals,":[117],"label":[118],"propagation":[119],"applied":[121],"2D":[123],"feature":[125,161],"projections.":[126],"Following":[127],"this,":[128],"pseudolabels":[129],"are":[130],"selected":[131],"under":[132],"curriculum-driven":[134],"policy,":[135],"while":[136],"oracle":[138],"annotates":[139],"most":[141],"These":[144],"contribute":[145],"composite":[148],"loss":[149],"function":[150],"combines":[152],"supervised":[153],"contrastive,":[154],"supervised,":[155],"semi-supervised":[157],"components-leading":[158],"enhanced":[160],"classification.":[165],"Evaluated":[166],"three":[168],"real-world":[169],"biological":[170],"datasets":[172],"amount":[176],"our":[180],"consistently":[182],"outperforms":[183],"baselines":[184],"approaches":[187],"improving":[189],"generalization":[190],"reducing":[192],"annotation":[193],"effort.":[194]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-11-11T00:00:00"}