{"id":"https://openalex.org/W4312390859","doi":"https://doi.org/10.1109/icpr56361.2022.9956182","title":"DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision","display_name":"DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision","publication_year":2022,"publication_date":"2022-08-21","ids":{"openalex":"https://openalex.org/W4312390859","doi":"https://doi.org/10.1109/icpr56361.2022.9956182"},"language":"en","primary_location":{"id":"doi:10.1109/icpr56361.2022.9956182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956182","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5120393122","display_name":"Erik Jakob Wallin","orcid":"https://orcid.org/0000-0002-4848-5540"},"institutions":[{"id":"https://openalex.org/I1339161553","display_name":"Saab (Switzerland)","ror":"https://ror.org/045rgx026","country_code":"CH","type":"company","lineage":["https://openalex.org/I1339161553","https://openalex.org/I4210153572"]},{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["CH","SE"],"is_corresponding":false,"raw_author_name":"Erik Wallin","raw_affiliation_strings":["Saab AB","Chalmers University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Saab AB","institution_ids":["https://openalex.org/I1339161553"]},{"raw_affiliation_string":"Chalmers University of Technology","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029413988","display_name":"Lennart Svensson","orcid":"https://orcid.org/0000-0003-0206-9186"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Lennart Svensson","raw_affiliation_strings":["Chalmers University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112556001","display_name":"Fredrik Kahl","orcid":null},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fredrik Kahl","raw_affiliation_strings":["Chalmers University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035123040","display_name":"Lars Hammarstrand","orcid":null},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Lars Hammarstrand","raw_affiliation_strings":["Chalmers University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology","institution_ids":["https://openalex.org/I66862912"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2871","last_page":"2877"},"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":0.9993000030517578,"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":0.9993000030517578,"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":0.9922999739646912,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.989799976348877,"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/computer-science","display_name":"Computer science","score":0.8395076990127563},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7955214977264404},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.6631518602371216},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6544147729873657},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6351344585418701},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.6255634427070618},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.6035542488098145},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.5310751795768738},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5114492177963257},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.49891209602355957},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.4846571087837219},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3620528280735016},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.15074628591537476}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8395076990127563},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7955214977264404},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.6631518602371216},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6544147729873657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6351344585418701},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.6255634427070618},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.6035542488098145},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.5310751795768738},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5114492177963257},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.49891209602355957},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.4846571087837219},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3620528280735016},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.15074628591537476},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/icpr56361.2022.9956182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr56361.2022.9956182","pdf_url":null,"source":{"id":"https://openalex.org/S4363607731","display_name":"2022 26th International Conference on Pattern Recognition (ICPR)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 26th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:research.chalmers.se:533731","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/533731","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"pmh:oai:research.chalmers.se:533889","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/946765bf-d601-4cb5-8f80-833c9019a76a","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4000000059604645,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1988529147","https://openalex.org/W2091146638","https://openalex.org/W2101210369","https://openalex.org/W2108598243","https://openalex.org/W2111316763","https://openalex.org/W2118858186","https://openalex.org/W2335728318","https://openalex.org/W2746314669","https://openalex.org/W2765407302","https://openalex.org/W2936995161","https://openalex.org/W2951970475","https://openalex.org/W2952229419","https://openalex.org/W2953070460","https://openalex.org/W2962369866","https://openalex.org/W2963037989","https://openalex.org/W2963263347","https://openalex.org/W2964137095","https://openalex.org/W2964159205","https://openalex.org/W2978426779","https://openalex.org/W2981381717","https://openalex.org/W2981952041","https://openalex.org/W2996501936","https://openalex.org/W3001197829","https://openalex.org/W3005680577","https://openalex.org/W3035060554","https://openalex.org/W3035524453","https://openalex.org/W3035682985","https://openalex.org/W3093071362","https://openalex.org/W3094502228","https://openalex.org/W3100859887","https://openalex.org/W3113757710","https://openalex.org/W3118608800","https://openalex.org/W3159481202","https://openalex.org/W3171007011","https://openalex.org/W3171608926","https://openalex.org/W3173770676","https://openalex.org/W3180562345","https://openalex.org/W3182493068","https://openalex.org/W3205500251","https://openalex.org/W3209458476","https://openalex.org/W3214101408","https://openalex.org/W4287388854","https://openalex.org/W4385245566","https://openalex.org/W6623329352","https://openalex.org/W6639102338","https://openalex.org/W6677919164","https://openalex.org/W6703116779","https://openalex.org/W6713132643","https://openalex.org/W6726497184","https://openalex.org/W6733814495","https://openalex.org/W6739901393","https://openalex.org/W6743428213","https://openalex.org/W6745136726","https://openalex.org/W6761030284","https://openalex.org/W6762913911","https://openalex.org/W6764051988","https://openalex.org/W6765939562","https://openalex.org/W6771787070","https://openalex.org/W6773005947","https://openalex.org/W6774314701","https://openalex.org/W6779326418","https://openalex.org/W6779977557","https://openalex.org/W6783991215","https://openalex.org/W6784333009","https://openalex.org/W6787972765","https://openalex.org/W6788329692","https://openalex.org/W6797119129","https://openalex.org/W6802864417","https://openalex.org/W6803183535"],"related_works":["https://openalex.org/W4312414840","https://openalex.org/W2794908468","https://openalex.org/W4206276646","https://openalex.org/W2943467239","https://openalex.org/W1571801203","https://openalex.org/W101422005","https://openalex.org/W192740413","https://openalex.org/W3004135598","https://openalex.org/W2952937263","https://openalex.org/W2168489430"],"abstract_inverted_index":{"Following":[0],"the":[1,42,95,103,111],"success":[2],"of":[3,18,33,41,73],"supervised":[4],"learning,":[5],"semi-supervised":[6],"learning":[7],"(SSL)":[8],"is":[9,15,76,137],"now":[10],"becoming":[11],"increasingly":[12],"popular.":[13],"SSL":[14,45,90,134],"a":[16,24,30,38,71,88,99],"family":[17],"methods,":[19],"which":[20,93],"in":[21,110],"addition":[22],"to":[23,105,132],"labeled":[25],"training":[26,58,112,129],"set,":[27],"also":[28,127],"use":[29],"sizable":[31],"collection":[32],"unlabeled":[34,80,108],"data":[35,81,109],"for":[36],"fitting":[37],"model.":[39],"Most":[40],"recent":[43],"successful":[44],"methods":[46,62],"are":[47,82],"based":[48],"on":[49,67,122],"pseudo-labeling":[50,96],"approaches:":[51],"letting":[52],"confident":[53],"model":[54,104],"predictions":[55],"act":[56],"as":[57],"labels.":[59],"While":[60],"these":[61],"have":[63],"shown":[64],"impressive":[65],"results":[66],"many":[68],"benchmark":[69,124],"datasets,":[70],"drawback":[72],"this":[74,117],"approach":[75],"that":[77,116],"not":[78],"all":[79,107],"used":[83],"during":[84],"training.":[85],"We":[86,114],"propose":[87],"new":[89],"algorithm,":[91],"DoubleMatch,":[92],"combines":[94],"technique":[97],"with":[98],"self-supervised":[100],"loss,":[101],"enabling":[102],"utilize":[106],"process.":[113],"show":[115],"method":[118],"achieves":[119],"state-of-the-art":[120],"accuracies":[121],"multiple":[123],"datasets":[125],"while":[126],"reducing":[128],"times":[130],"compared":[131],"existing":[133],"methods.":[135],"Code":[136],"available":[138],"at":[139],"https://github.com/walline/doublematch.":[140]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}