{"id":"https://openalex.org/W4390993854","doi":"https://doi.org/10.1145/3630138.3630529","title":"Uncovering Self-Supervised Learning: From Current Applications to Future Trends","display_name":"Uncovering Self-Supervised Learning: From Current Applications to Future Trends","publication_year":2023,"publication_date":"2023-09-24","ids":{"openalex":"https://openalex.org/W4390993854","doi":"https://doi.org/10.1145/3630138.3630529"},"language":"en","primary_location":{"id":"doi:10.1145/3630138.3630529","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3630138.3630529","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Power Communication Computing and Networking Technologies","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/A5103064917","display_name":"Pan Zhang","orcid":"https://orcid.org/0009-0005-2632-2109"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]},{"id":"https://openalex.org/I18570673","display_name":"Guangxi University of Science and Technology","ror":"https://ror.org/02fj6b627","country_code":"CN","type":"education","lineage":["https://openalex.org/I18570673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pan Zhang","raw_affiliation_strings":["Guangxi University of Science and Technology, College of Automation, China"],"raw_orcid":"https://orcid.org/0009-0005-2632-2109","affiliations":[{"raw_affiliation_string":"Guangxi University of Science and Technology, College of Automation, China","institution_ids":["https://openalex.org/I150807315","https://openalex.org/I18570673"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100777430","display_name":"Qiwen He","orcid":"https://orcid.org/0000-0001-8571-4018"},"institutions":[{"id":"https://openalex.org/I4210161599","display_name":"Hechi University","ror":"https://ror.org/05pjkyk24","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210161599"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiwen He","raw_affiliation_strings":["Hechi University, College of Artificial Intelligence and Manufacturing, China"],"raw_orcid":"https://orcid.org/0000-0001-8571-4018","affiliations":[{"raw_affiliation_string":"Hechi University, College of Artificial Intelligence and Manufacturing, China","institution_ids":["https://openalex.org/I4210161599"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiaofei Ai","orcid":"https://orcid.org/0009-0005-5878-3129"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]},{"id":"https://openalex.org/I18570673","display_name":"Guangxi University of Science and Technology","ror":"https://ror.org/02fj6b627","country_code":"CN","type":"education","lineage":["https://openalex.org/I18570673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaofei Ai","raw_affiliation_strings":["Guangxi University of Science and Technology, College of Automation, China"],"raw_orcid":"https://orcid.org/0009-0005-5878-3129","affiliations":[{"raw_affiliation_string":"Guangxi University of Science and Technology, College of Automation, China","institution_ids":["https://openalex.org/I150807315","https://openalex.org/I18570673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045463670","display_name":"Fuxing Ma","orcid":"https://orcid.org/0009-0009-7389-9516"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]},{"id":"https://openalex.org/I18570673","display_name":"Guangxi University of Science and Technology","ror":"https://ror.org/02fj6b627","country_code":"CN","type":"education","lineage":["https://openalex.org/I18570673"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fuxing Ma","raw_affiliation_strings":["Guangxi University of Science and Technology, College of Automation, China"],"raw_orcid":"https://orcid.org/0009-0009-7389-9516","affiliations":[{"raw_affiliation_string":"Guangxi University of Science and Technology, College of Automation, China","institution_ids":["https://openalex.org/I150807315","https://openalex.org/I18570673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1632,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59447036,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9994000196456909,"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":0.9994000196456909,"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":0.9929999709129333,"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":0.9829999804496765,"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":0.7638475894927979},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7439513802528381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7267465591430664},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5952099561691284},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.5573121905326843},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4413840174674988}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7638475894927979},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7439513802528381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7267465591430664},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5952099561691284},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.5573121905326843},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4413840174674988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3630138.3630529","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3630138.3630529","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Conference on Power Communication Computing and Networking Technologies","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2526468814","https://openalex.org/W2769112066","https://openalex.org/W2798991696","https://openalex.org/W2895951708","https://openalex.org/W2963037989","https://openalex.org/W2963420272","https://openalex.org/W2971432438","https://openalex.org/W3011411500","https://openalex.org/W3035524453","https://openalex.org/W3036642894","https://openalex.org/W3095867871","https://openalex.org/W3114632476","https://openalex.org/W3115652744","https://openalex.org/W3127238141","https://openalex.org/W3128209463","https://openalex.org/W3130441769","https://openalex.org/W3133518153","https://openalex.org/W4220901260","https://openalex.org/W4223948957","https://openalex.org/W4285211963","https://openalex.org/W4287729879","https://openalex.org/W4313139981","https://openalex.org/W4322618544","https://openalex.org/W4382701166"],"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/W4313488044","https://openalex.org/W3209574120","https://openalex.org/W4390062853","https://openalex.org/W4389256085"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"require":[3],"large":[4,75],"amounts":[5],"of":[6,73,77,98,121,147,166,170,174,196],"labelled":[7],"data":[8,27,39,54,79],"for":[9,60,131],"training":[10,110],"so":[11],"that":[12],"the":[13,74,118,143,167,171,189,193],"models":[14],"can":[15],"be":[16],"applied":[17],"more":[18,202],"accurately":[19],"to":[20,69,188],"specific":[21],"tasks.":[22],"However,":[23],"in":[24,42,51,85,134,140,192],"reality,":[25],"obtaining":[26],"with":[28],"detailed":[29],"labelling":[30],"is":[31,40,46,185],"quite":[32],"expensive":[33],"and":[34,115,123,136,177,180],"difficult.":[35],"In":[36,88],"contrast,":[37],"unlabelled":[38,53,78,86,206],"available":[41],"abundance.":[43],"Self-supervised":[44],"learning":[45,49,61,129,149,176],"a":[47,57,163],"machine":[48],"method":[50,67],"which":[52,199],"acts":[55],"as":[56],"supervisory":[58],"signal":[59],"using":[62],"its":[63],"own":[64],"information.":[65],"The":[66,182],"tries":[68],"make":[70],"full":[71],"use":[72],"amount":[76],"by":[80,127],"capturing":[81],"deeper,":[82],"higher-order":[83],"features":[84],"data.":[87],"this":[89,158],"paper,":[90,159],"we":[91,160],"first":[92],"review":[93],"several":[94],"typical":[95],"design":[96,168],"ideas":[97,169],"self-supervised":[99,128,148,175,197],"learning,":[100,198],"summarising":[101],"them":[102],"into":[103],"three":[104,172],"main":[105],"categories":[106],"based":[107,153],"on":[108,154,204],"their":[109,178],"methods:":[111],"end-to-end,":[112],"memory":[113],"bank":[114],"momentum.":[116],"Then,":[117],"current":[119,124],"state":[120],"research":[122,145,183],"challenges":[125],"faced":[126],"algorithms":[130,150],"common":[132],"tasks":[133],"NLP":[135],"CV":[137],"are":[138,151],"summarised":[139],"segments.":[141],"Finally,":[142],"future":[144],"directions":[146],"envisioned":[152],"these":[155],"challenges.":[156],"Through":[157],"have":[161],"gained":[162],"deeper":[164],"understanding":[165],"systems":[173],"advantages":[179],"disadvantages.":[181],"direction":[184],"indicated":[186],"according":[187],"difficulties":[190],"encountered":[191],"practical":[194],"application":[195],"makes":[200],"it":[201],"promising":[203],"large-scale":[205],"datasets.":[207]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
