{"id":"https://openalex.org/W4281640725","doi":"https://doi.org/10.1145/3529399.3529419","title":"Evaluating the FixMatch Semi-Supervised Algorithm for Unbalanced Image Data","display_name":"Evaluating the FixMatch Semi-Supervised Algorithm for Unbalanced Image Data","publication_year":2022,"publication_date":"2022-03-11","ids":{"openalex":"https://openalex.org/W4281640725","doi":"https://doi.org/10.1145/3529399.3529419"},"language":"en","primary_location":{"id":"doi:10.1145/3529399.3529419","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3529399.3529419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Machine Learning Technologies (ICMLT)","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/A5066329186","display_name":"Ali Reza Sajun","orcid":"https://orcid.org/0000-0003-1270-3005"},"institutions":[{"id":"https://openalex.org/I199440890","display_name":"American University of Sharjah","ror":"https://ror.org/001g2fj96","country_code":"AE","type":"education","lineage":["https://openalex.org/I199440890"]}],"countries":["AE"],"is_corresponding":true,"raw_author_name":"Ali Reza Mohammed Husein Sajun","raw_affiliation_strings":["Department of Computer Science and Engineering, American University of Sharjah, UAE"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, American University of Sharjah, UAE","institution_ids":["https://openalex.org/I199440890"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104075637","display_name":"Imran Ahmed Zualkernan","orcid":null},"institutions":[{"id":"https://openalex.org/I199440890","display_name":"American University of Sharjah","ror":"https://ror.org/001g2fj96","country_code":"AE","type":"education","lineage":["https://openalex.org/I199440890"]}],"countries":["AE"],"is_corresponding":false,"raw_author_name":"Imran Ahmed Zualkernan","raw_affiliation_strings":["Department of Computer Science and Engineering, American University of Sharjah, UAE"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, American University of Sharjah, UAE","institution_ids":["https://openalex.org/I199440890"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066329186"],"corresponding_institution_ids":["https://openalex.org/I199440890"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.05261102,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"119","last_page":"123"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9987000226974487,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9987000226974487,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9918000102043152,"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/benchmarking","display_name":"Benchmarking","score":0.8968298435211182},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6844823956489563},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.6382176280021667},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5864786505699158},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5863826870918274},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5011293888092041},{"id":"https://openalex.org/keywords/principle-of-maximum-entropy","display_name":"Principle of maximum entropy","score":0.4557170867919922},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4539295732975006},{"id":"https://openalex.org/keywords/mean-absolute-error","display_name":"Mean absolute error","score":0.4387419819831848},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4122636914253235},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3965384364128113},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36886361241340637},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34185582399368286},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.3341600298881531},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22484633326530457},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1829041838645935}],"concepts":[{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.8968298435211182},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6844823956489563},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.6382176280021667},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5864786505699158},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5863826870918274},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5011293888092041},{"id":"https://openalex.org/C9679016","wikidata":"https://www.wikidata.org/wiki/Q1417473","display_name":"Principle of maximum entropy","level":2,"score":0.4557170867919922},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4539295732975006},{"id":"https://openalex.org/C188154048","wikidata":"https://www.wikidata.org/wiki/Q6803609","display_name":"Mean absolute error","level":3,"score":0.4387419819831848},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4122636914253235},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3965384364128113},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36886361241340637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34185582399368286},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.3341600298881531},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22484633326530457},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1829041838645935},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3529399.3529419","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3529399.3529419","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 7th International Conference on Machine Learning Technologies (ICMLT)","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":31,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2335728318","https://openalex.org/W2551429935","https://openalex.org/W2767106145","https://openalex.org/W2794523151","https://openalex.org/W2911495555","https://openalex.org/W2936503027","https://openalex.org/W2943865428","https://openalex.org/W2962369866","https://openalex.org/W2971644666","https://openalex.org/W2972488238","https://openalex.org/W2981660215","https://openalex.org/W2984353870","https://openalex.org/W2989700832","https://openalex.org/W2996690341","https://openalex.org/W3001197829","https://openalex.org/W3091401866","https://openalex.org/W3096659298","https://openalex.org/W3097217077","https://openalex.org/W3118608800","https://openalex.org/W3178268517","https://openalex.org/W3197886029","https://openalex.org/W3204365647","https://openalex.org/W3205040413","https://openalex.org/W3207361716","https://openalex.org/W4212774754","https://openalex.org/W6713132643","https://openalex.org/W6774190225","https://openalex.org/W6779659972","https://openalex.org/W6791493996","https://openalex.org/W6792576804"],"related_works":["https://openalex.org/W4238897586","https://openalex.org/W435179959","https://openalex.org/W2619091065","https://openalex.org/W2059640416","https://openalex.org/W1490753184","https://openalex.org/W2284465472","https://openalex.org/W2291782699","https://openalex.org/W1993948687","https://openalex.org/W2000169967","https://openalex.org/W2112883198"],"abstract_inverted_index":{"In":[0],"recent":[1],"years":[2],"there":[3,127],"has":[4],"been":[5],"a":[6,74,100,129,150],"major":[7],"rise":[8],"in":[9,11,111,124,147],"interest":[10],"the":[12,26,61,64,85,117,136,139,144,159],"field":[13],"of":[14,50,63,82,87,132,155],"semi-supervised":[15],"deep":[16],"learning":[17],"with":[18,84,120,149],"newer":[19],"techniques":[20],"being":[21],"proposed":[22],"which":[23,51,102],"rapidly":[24],"push":[25],"state-of-the-art.":[27],"Most":[28],"techniques,":[29],"however,":[30],"use":[31],"balanced":[32,107],"benchmarking":[33,71],"datasets":[34,72,119],"such":[35],"as":[36],"CIFAR":[37],"and":[38,40,73,97],"SVHN":[39],"therefore":[41],"do":[42],"not":[43],"translate":[44],"into":[45,60],"real":[46,75],"life":[47],"applications,":[48],"many":[49],"involve":[52],"highly":[53],"imbalanced":[54,118],"datasets.":[55],"An":[56,109],"investigation":[57],"was":[58,103],"conducted":[59],"performance":[62,148],"FixMatch":[65],"algorithm":[66],"when":[67],"trained":[68],"on":[69,105],"unbalanced":[70],"world":[76],"dataset.":[77],"Three":[78],"different":[79],"entropy-based":[80],"distributions":[81],"imbalance,":[83],"proportion":[86],"labeled":[88],"samples":[89],"varied":[90],"from":[91],"80%":[92],"to":[93,99,158],"40%,":[94],"were":[95],"applied":[96],"compared":[98,157],"baseline":[101],"computed":[104],"uniformly":[106],"data.":[108],"increase":[110,154],"error":[112,152],"rate":[113,153],"is":[114],"noted":[115],"for":[116],"larger":[121],"errors":[122],"seen":[123],"cases":[125],"where":[126],"are":[128],"greater":[130],"number":[131],"minority":[133,141],"classes.":[134],"Indeed,":[135],"distribution":[137],"containing":[138],"most":[140],"classes":[142],"showed":[143],"maximum":[145],"drop":[146],"mean":[151],"12.67%":[156],"uniform":[160],"baseline.":[161]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-18T07:56:08.524223","created_date":"2025-10-10T00:00:00"}