{"id":"https://openalex.org/W4416887504","doi":"https://doi.org/10.5753/jbcs.2026.5883","title":"Co-Training with Active Contrastive Learning and Meta-Pseudo-Labeling on 2D Projections for Deep Semi-Supervised Learning","display_name":"Co-Training with Active Contrastive Learning and Meta-Pseudo-Labeling on 2D Projections for Deep Semi-Supervised Learning","publication_year":2026,"publication_date":"2026-06-10","ids":{"openalex":"https://openalex.org/W4416887504","doi":"https://doi.org/10.5753/jbcs.2026.5883"},"language":"en","primary_location":{"id":"doi:10.5753/jbcs.2026.5883","is_oa":true,"landing_page_url":"https://doi.org/10.5753/jbcs.2026.5883","pdf_url":null,"source":{"id":"https://openalex.org/S69801987","display_name":"Journal of the Brazilian Computer Society","issn_l":"0104-6500","issn":["0104-6500","1678-4804"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Brazilian Computer Society","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5753/jbcs.2026.5883","any_repository_has_fulltext":true},"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":false,"raw_author_name":"David Aparco-Cardenas","raw_affiliation_strings":["University of Campinas"],"raw_orcid":"https://orcid.org/0000-0003-2537-7050","affiliations":[{"raw_affiliation_string":"University of Campinas","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":["University of Campinas"],"raw_orcid":"https://orcid.org/0000-0002-2466-7315","affiliations":[{"raw_affiliation_string":"University of Campinas","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":["University of Campinas"],"raw_orcid":"https://orcid.org/0000-0002-2914-5380","affiliations":[{"raw_affiliation_string":"University of Campinas","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":["University of Campinas"],"raw_orcid":"https://orcid.org/0000-0002-9529-4253","affiliations":[{"raw_affiliation_string":"University of Campinas","institution_ids":["https://openalex.org/I181391015"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I181391015"],"apc_list":{"value":1390,"currency":"USD","value_usd":1390},"apc_paid":{"value":1390,"currency":"USD","value_usd":1390},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01863846,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"32","issue":"1","first_page":"1523","last_page":"1538"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.2784000039100647,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.2784000039100647,"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":0.17190000414848328,"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":0.11140000075101852,"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/annotation","display_name":"Annotation","score":0.6951000094413757},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6062999963760376},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4936999976634979},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.49059998989105225},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4869000017642975},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.48260000348091125},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.47519999742507935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46070000529289246}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7310000061988831},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6951000094413757},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6715999841690063},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6062999963760376},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5127999782562256},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4936999976634979},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.49059998989105225},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4869000017642975},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.48260000348091125},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.47519999742507935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46070000529289246},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3901999890804291},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.357699990272522},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.35249999165534973},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.33570000529289246},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.3142000138759613},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.2793000042438507},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.2549000084400177}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.5753/jbcs.2026.5883","is_oa":true,"landing_page_url":"https://doi.org/10.5753/jbcs.2026.5883","pdf_url":null,"source":{"id":"https://openalex.org/S69801987","display_name":"Journal of the Brazilian Computer Society","issn_l":"0104-6500","issn":["0104-6500","1678-4804"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Brazilian Computer Society","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2504.18666","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2504.18666","pdf_url":"https://arxiv.org/pdf/2504.18666","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2504.18666","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2504.18666","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.5753/jbcs.2026.5883","is_oa":true,"landing_page_url":"https://doi.org/10.5753/jbcs.2026.5883","pdf_url":null,"source":{"id":"https://openalex.org/S69801987","display_name":"Journal of the Brazilian Computer Society","issn_l":"0104-6500","issn":["0104-6500","1678-4804"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of the Brazilian Computer Society","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1139104289","display_name":null,"funder_award_id":"2014/12236-1","funder_id":"https://openalex.org/F4320321091","funder_display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior"},{"id":"https://openalex.org/G2068960743","display_name":null,"funder_award_id":"313329/2020-6","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G2486662831","display_name":null,"funder_award_id":"2013/07375-","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/G2823776494","display_name":null,"funder_award_id":"88887","funder_id":"https://openalex.org/F4320321091","funder_display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior"},{"id":"https://openalex.org/G3572101131","display_name":null,"funder_award_id":"2014/","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/G361160742","display_name":null,"funder_award_id":"304711/2023-3","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G390121578","display_name":null,"funder_award_id":"2013/07375-0","funder_id":"https://openalex.org/F4320321091","funder_display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior"},{"id":"https://openalex.org/G4312984384","display_name":null,"funder_award_id":"2014/12236-1","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/G5867257752","display_name":null,"funder_award_id":"2023/14427-8","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/G5990746028","display_name":null,"funder_award_id":"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/G6191138830","display_name":null,"funder_award_id":"88887","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/G6669552033","display_name":null,"funder_award_id":"2013/07375-0","funder_id":"https://openalex.org/F4320322025","funder_display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico"},{"id":"https://openalex.org/G7285438780","display_name":null,"funder_award_id":"2014/12236-1","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/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"},{"id":"https://openalex.org/F4320322025","display_name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","ror":"https://ror.org/03swz6y49"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"A":[0],"major":[1],"challenge":[2,52],"that":[3,110,149],"prevents":[4],"the":[5,12,83,94,174,191,195,200,213,222,242],"training":[6],"of":[7,15,18,86,96,130,132,136,168,194,263,285,291],"deep":[8,141,197],"learning":[9,49,119],"models":[10],"is":[11,24,38,89,188,249],"limited":[13],"availability":[14],"large":[16,71],"quantities":[17],"accurately":[19],"labeled":[20,57,87,133,169,223,264,292],"data.":[21,138,293],"This":[22],"shortcoming":[23],"particularly":[25],"acute":[26],"in":[27,128,208],"areas":[28],"such":[29],"as":[30],"medical":[31],"and":[32,42,58,70,117,134,181,219,237,268],"biological":[33],"sciences":[34],"where":[35],"data":[36,88],"annotation":[37,143,277],"an":[39,229],"expert-demanding,":[40],"time-consuming,":[41],"error-prone":[43],"undertaking.":[44],"In":[45,81,273],"this":[46,51],"regard,":[47],"semi-supervised":[48,238],"tackles":[50],"by":[53,171,279],"capitalizing":[54],"on":[55,67,190,251],"scarce":[56],"abundant":[59],"unlabeled":[60,137],"data;":[61],"however,":[62],"state-of-the-art":[63],"methods":[64],"typically":[65],"depend":[66],"pre-trained":[68],"features":[69],"validation":[72],"sets":[73],"to":[74,120,154,221,283],"learn":[75],"effective":[76],"representations":[77,243],"for":[78,125,244],"classification":[79,127],"tasks.":[80],"addition,":[82,274],"reduced":[84,166],"set":[85,167],"often":[90],"randomly":[91],"sampled,":[92],"neglecting":[93],"selection":[95],"more":[97],"informative":[98],"samples.":[99],"Here,":[100],"we":[101],"present":[102],"active":[103,118],"Deep":[104],"Feature":[105],"Annotation":[106],"(active-DeepFA),":[107],"a":[108,146,165,209],"method":[109,162],"effectively":[111],"combines":[112],"contrastive":[113,178],"learning,":[114],"teacher-student-based":[115],"meta-pseudo-labeling":[116],"train":[121],"non-pre-trained":[122],"CNN":[123],"architectures":[124],"image":[126,245,254],"scenarios":[129],"scarcity":[131],"abundance":[135],"It":[139],"integrates":[140],"feature":[142],"(DeepFA)":[144],"into":[145],"co-training":[147],"setup":[148],"implements":[150],"two":[151],"cooperative":[152],"networks":[153,175,207,226],"mitigate":[155],"confirmation":[156],"bias":[157],"arising":[158],"from":[159],"pseudo-labels.":[160],"The":[161,225],"starts":[163],"with":[164,176,260,288],"samples":[170,216],"warming":[172],"up":[173],"supervised":[177,234],"learning.":[179],"Afterward":[180],"at":[182],"regular":[183],"epoch":[184],"intervals,":[185],"label":[186],"propagation":[187],"performed":[189],"2D":[192],"projections":[193],"networks'":[196],"features.":[198],"Next,":[199],"most":[201,214],"reliable":[202],"pseudo-labels":[203],"are":[204,217],"exchanged":[205],"between":[206],"cross-training":[210],"fashion,":[211],"while":[212],"meaningful":[215],"annotated":[218],"added":[220],"set.":[224],"independently":[227],"minimize":[228],"objective":[230],"loss":[231,239],"function":[232],"comprising":[233],"contrastive,":[235],"supervised,":[236],"components,":[240],"enhancing":[241],"classification.":[246],"Our":[247],"approach":[248],"evaluated":[250],"seven":[252,270],"challenging":[253],"datasets":[255],"across":[256],"three":[257],"distinct":[258],"domains":[259],"only":[261,289],"5%":[262],"samples,":[265],"surpassing":[266],"baselines":[267],"outperforming":[269],"established":[271],"benchmarks.":[272],"it":[275],"reduces":[276],"effort":[278],"achieving":[280],"comparable":[281],"results":[282],"those":[284],"its":[286],"counterparts":[287],"3%":[290]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}
