{"id":"https://openalex.org/W4403535143","doi":"https://doi.org/10.1109/sibgrapi62404.2024.10716313","title":"Contrastive Learning and Iterative Meta-Pseudo-Labeling on 2D Projections for Deep Semi-Supervised Learning","display_name":"Contrastive Learning and Iterative Meta-Pseudo-Labeling on 2D Projections for Deep Semi-Supervised Learning","publication_year":2024,"publication_date":"2024-09-30","ids":{"openalex":"https://openalex.org/W4403535143","doi":"https://doi.org/10.1109/sibgrapi62404.2024.10716313"},"language":"en","primary_location":{"id":"doi:10.1109/sibgrapi62404.2024.10716313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sibgrapi62404.2024.10716313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 37th 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":0.3944,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58496372,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"3","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.8355000019073486,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.8355000019073486,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13731","display_name":"Advanced Computing and Algorithms","score":0.7971000075340271,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.7549999952316284,"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":0.7344311475753784},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6962524652481079},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5857748985290527},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.4833378493785858},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4528367221355438},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3660084009170532},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3585822582244873}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7344311475753784},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6962524652481079},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5857748985290527},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.4833378493785858},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4528367221355438},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3660084009170532},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3585822582244873}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sibgrapi62404.2024.10716313","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sibgrapi62404.2024.10716313","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 37th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI)","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":16,"referenced_works":["https://openalex.org/W1969328404","https://openalex.org/W2398616336","https://openalex.org/W2732036031","https://openalex.org/W2964159205","https://openalex.org/W3080132074","https://openalex.org/W3091002423","https://openalex.org/W3136021864","https://openalex.org/W3152264159","https://openalex.org/W3198266240","https://openalex.org/W4287322212","https://openalex.org/W4367396468","https://openalex.org/W6733814495","https://openalex.org/W6764051988","https://openalex.org/W6765939562","https://openalex.org/W6773005947","https://openalex.org/W6842024468"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W4380075502","https://openalex.org/W2513638114","https://openalex.org/W4390062853","https://openalex.org/W2340127552","https://openalex.org/W4389256085","https://openalex.org/W3210156800","https://openalex.org/W3033485676"],"abstract_inverted_index":{"The":[0],"scarcity":[1],"of":[2,10,83,137,145,178,217,237],"accurately":[3],"labeled":[4,85,168,238],"data":[5,24,118],"critically":[6],"hampers":[7],"the":[8,116,134,143,152,172,185,188,199,214,218],"usage":[9],"deep":[11,182],"learning":[12,131,259],"models.":[13],"This":[14],"issue":[15],"is":[16,225],"highlighted":[17],"in":[18,27,41,81,107,110,202],"areas":[19],"(e.g.,":[20],"biological":[21,230],"sciences)":[22],"where":[23,162],"annotation":[25],"results":[26],"an":[28,67,111],"expert-demanding,":[29],"labor-intensive":[30],"and":[31,50,86,119,210,243,251],"error-prone":[32],"task.":[33],"While":[34],"state-of-the-art":[35,253],"semi-supervised":[36,258],"approaches":[37],"have":[38],"proven":[39],"effective":[40,56],"circumventing":[42],"this":[43,63],"limitation,":[44],"their":[45],"reliance":[46],"on":[47,93,129,171,227],"pre-trained":[48,146],"architectures":[49,77],"large":[51],"validation":[52,95],"sets":[53],"to":[54,114,132,169,197,247],"deliver":[55],"solutions":[57],"still":[58],"poses":[59],"a":[60,94,102,121,157,203],"challenge.":[61],"In":[62],"work":[64],"we":[65],"introduce":[66],"iterative":[68],"contrastive-based":[69],"meta-pseudo-Iabeling":[70],"method":[71,224],"for":[72,78],"training":[73],"non-pre-trained":[74],"custom":[75],"CNN":[76],"image":[79,231],"classification":[80],"conditions":[82],"limited":[84],"abundant":[87],"unlabeled":[88,117,170],"data,":[89],"with":[90,187,233],"no":[91],"dependency":[92],"set.":[96],"It":[97],"generates":[98],"multiple":[99],"models":[100],"across":[101],"few":[103],"iterations,":[104],"which":[105],"are":[106,154,195],"turn":[108],"exploited":[109],"ensemble":[112],"manner":[113],"label":[115],"train":[120],"final":[122],"classifier.":[123],"Our":[124,223],"approach":[125],"starts":[126],"by":[127],"capitalizing":[128],"contrastive":[130],"enhance":[133],"representation":[135],"ability":[136,216],"two":[138,248],"collaborative":[139],"networks":[140,153,219],"while":[141,212],"eliminating":[142],"need":[144],"architectures.":[147],"Then,":[148],"during":[149],"each":[150,179],"iteration,":[151],"trained":[155],"within":[156],"teacher-student":[158],"based":[159],"cross-training":[160,204],"setup,":[161],"OPFSemi":[163],"(teacher)":[164],"propagates":[165],"labels":[166],"from":[167,255],"non-linear":[173],"2D":[174],"latent":[175],"space":[176],"projections":[177],"network's":[180],"(student)":[181],"features;":[183],"afterward,":[184],"pseudo-labels":[186],"highest":[189],"top":[190],"10%":[191],"confidence,":[192],"per":[193],"class,":[194],"picked":[196],"fine-tune":[198],"other":[200],"network":[201],"manner,":[205],"jointly":[206],"mitigating":[207],"confirmation":[208],"bias":[209],"overfitting":[211],"improving":[213],"generalization":[215],"as":[220],"iterations":[221],"evolve.":[222],"evaluated":[226],"three":[228,256],"challenging":[229],"datasets":[232],"only":[234],"5":[235],"%":[236],"samples,":[239],"demonstrating":[240],"its":[241],"effectiveness":[242],"robustness":[244],"when":[245],"compared":[246],"direct":[249],"baselines":[250],"six":[252],"methods":[254],"different":[257],"paradigms.":[260]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}