{"id":"https://openalex.org/W4391997109","doi":"https://doi.org/10.3390/a17030091","title":"Multi-Augmentation-Based Contrastive Learning for Semi-Supervised Learning","display_name":"Multi-Augmentation-Based Contrastive Learning for Semi-Supervised Learning","publication_year":2024,"publication_date":"2024-02-20","ids":{"openalex":"https://openalex.org/W4391997109","doi":"https://doi.org/10.3390/a17030091"},"language":"en","primary_location":{"id":"doi:10.3390/a17030091","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a17030091","pdf_url":"https://www.mdpi.com/1999-4893/17/3/91/pdf?version=1708426695","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1999-4893/17/3/91/pdf?version=1708426695","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102804283","display_name":"Jie Wang","orcid":"https://orcid.org/0009-0003-8298-791X"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Wang","raw_affiliation_strings":["Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou 310018, China"],"raw_orcid":"https://orcid.org/0009-0003-8298-791X","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101418881","display_name":"Jie Yang","orcid":"https://orcid.org/0000-0002-5465-6772"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jie Yang","raw_affiliation_strings":["Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou 310018, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I50760025"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101300665","display_name":"Jiafan He","orcid":"https://orcid.org/0009-0008-0815-5783"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiafan He","raw_affiliation_strings":["Science and Technology on Information Systems Engineering Laboratory, Nanjing 210014, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology on Information Systems Engineering Laboratory, Nanjing 210014, China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5041017781","display_name":"Dongliang Peng","orcid":"https://orcid.org/0000-0002-5549-2511"},"institutions":[{"id":"https://openalex.org/I50760025","display_name":"Hangzhou Dianzi University","ror":"https://ror.org/0576gt767","country_code":"CN","type":"education","lineage":["https://openalex.org/I50760025"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongliang Peng","raw_affiliation_strings":["Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou 310018, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Artificial Intelligence Institute, Hangzhou Dianzi University, Hangzhou 310018, China","institution_ids":["https://openalex.org/I50760025"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101418881"],"corresponding_institution_ids":["https://openalex.org/I50760025"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1782},"fwci":0.9737,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.77882294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"17","issue":"3","first_page":"91","last_page":"91"},"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":0.9995999932289124,"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":0.9995999932289124,"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/T12676","display_name":"Machine Learning and ELM","score":0.9944000244140625,"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/T10057","display_name":"Face and Expression Recognition","score":0.9926999807357788,"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":0.64955735206604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5832160711288452},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.516755998134613},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4479790925979614},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4271087348461151},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.4103265702724457}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.64955735206604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5832160711288452},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.516755998134613},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4479790925979614},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4271087348461151},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.4103265702724457}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/a17030091","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a17030091","pdf_url":"https://www.mdpi.com/1999-4893/17/3/91/pdf?version=1708426695","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:329a31405ffe4fe388f47a5e31b0815a","is_oa":true,"landing_page_url":"https://doaj.org/article/329a31405ffe4fe388f47a5e31b0815a","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Algorithms, Vol 17, Iss 3, p 91 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/a17030091","is_oa":true,"landing_page_url":"https://doi.org/10.3390/a17030091","pdf_url":"https://www.mdpi.com/1999-4893/17/3/91/pdf?version=1708426695","source":{"id":"https://openalex.org/S190629608","display_name":"Algorithms","issn_l":"1999-4893","issn":["1999-4893"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Algorithms","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1515287678","display_name":null,"funder_award_id":"GK229909299001-024","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1550846934","display_name":null,"funder_award_id":"U22A2047","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8730775042","display_name":null,"funder_award_id":"GK229909299001-024","funder_id":"https://openalex.org/F4554350417","funder_display_name":"Fundamental Research Funds for the Provincial Universities of Zhejiang"},{"id":"https://openalex.org/G8951932347","display_name":null,"funder_award_id":"05202206","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4554350417","display_name":"Fundamental Research Funds for the Provincial Universities of Zhejiang","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4391997109.pdf","grobid_xml":"https://content.openalex.org/works/W4391997109.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W1968817125","https://openalex.org/W2079057609","https://openalex.org/W2108598243","https://openalex.org/W2335728318","https://openalex.org/W2592691248","https://openalex.org/W2808462996","https://openalex.org/W2919115771","https://openalex.org/W2937073519","https://openalex.org/W2943865428","https://openalex.org/W2947298857","https://openalex.org/W2954996726","https://openalex.org/W2964137095","https://openalex.org/W2964159205","https://openalex.org/W2966415767","https://openalex.org/W2984353870","https://openalex.org/W2998508940","https://openalex.org/W3026859415","https://openalex.org/W3035160371","https://openalex.org/W3035682985","https://openalex.org/W3109620645","https://openalex.org/W3162739830","https://openalex.org/W3171581326","https://openalex.org/W3172507542","https://openalex.org/W3173770676","https://openalex.org/W3186323753","https://openalex.org/W4220826571","https://openalex.org/W4281627997","https://openalex.org/W4306836273","https://openalex.org/W4307823382","https://openalex.org/W4313041774","https://openalex.org/W4313138032","https://openalex.org/W4323266540","https://openalex.org/W4361276789","https://openalex.org/W4386546994","https://openalex.org/W4388634524","https://openalex.org/W4388672509","https://openalex.org/W4388695325","https://openalex.org/W6678975374","https://openalex.org/W6763015118","https://openalex.org/W6777906095","https://openalex.org/W6795215803","https://openalex.org/W6838360585"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W3046775127","https://openalex.org/W3107602296","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347","https://openalex.org/W4210805261"],"abstract_inverted_index":{"Semi-supervised":[0],"learning":[1,22,99],"has":[2],"been":[3],"proven":[4],"to":[5,12,117,136],"be":[6],"effective":[7],"in":[8,40],"utilizing":[9],"unlabeled":[10,27,115,142],"samples":[11,28,46],"mitigate":[13],"the":[14,31,72,132],"problem":[15],"of":[16,71,170],"limited":[17],"labeled":[18,35,45,140,171],"data.":[19],"Traditional":[20],"semi-supervised":[21,98],"methods":[23,82],"generate":[24,118],"pseudo-labels":[25],"for":[26,47,67],"and":[29,36,87,112,129,141,149],"train":[30],"classifier":[32,49],"using":[33],"both":[34],"pseudo-labeled":[37],"samples.":[38,172],"However,":[39,80],"data-scarce":[41],"scenarios,":[42],"reliance":[43],"on":[44,56,164],"initial":[48],"generation":[50],"can":[51],"degrade":[52],"performance.":[53],"Methods":[54],"based":[55],"consistency":[57,123,145],"regularization":[58],"have":[59],"shown":[60],"promising":[61],"results":[62],"by":[63],"encouraging":[64],"consistent":[65],"outputs":[66,109,128,138,148],"different":[68],"semantic":[69],"variations":[70],"same":[73],"sample":[74],"obtained":[75],"through":[76,160],"diverse":[77],"augmentation":[78,89],"techniques.":[79],"existing":[81],"typically":[83],"utilize":[84],"only":[85],"weak":[86],"strong":[88],"variants,":[90],"limiting":[91],"information":[92],"extraction.":[93],"Therefore,":[94],"a":[95,156],"multi-augmentation":[96],"contrastive":[97],"method":[100,154],"(MAC-SSL)":[101],"is":[102,134],"proposed.":[103],"MAC-SSL":[104],"introduces":[105],"moderate":[106],"augmentation,":[107],"combining":[108],"from":[110,139],"moderately":[111],"weakly":[113],"augmented":[114,126],"images":[116],"pseudo-labels.":[119,130,151],"Cross-entropy":[120],"loss":[121],"ensures":[122],"between":[124,146],"strongly":[125],"image":[127],"Furthermore,":[131],"MixUP":[133],"adopted":[135],"blend":[137],"images,":[143],"enhancing":[144],"re-augmented":[147],"new":[150],"The":[152],"proposed":[153],"achieves":[155],"state-of-the-art":[157],"performance":[158],"(accuracy)":[159],"extensive":[161],"experiments":[162],"conducted":[163],"multiple":[165],"datasets":[166],"with":[167],"varying":[168],"numbers":[169],"Ablation":[173],"studies":[174],"further":[175],"investigate":[176],"each":[177],"component\u2019s":[178],"significance.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":4}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}