{"id":"https://openalex.org/W4402264592","doi":"https://doi.org/10.1109/access.2024.3454753","title":"Unsupervised Visual Anomaly Detection Using Self-Supervised Pre-Trained Transformer","display_name":"Unsupervised Visual Anomaly Detection Using Self-Supervised Pre-Trained Transformer","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4402264592","doi":"https://doi.org/10.1109/access.2024.3454753"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3454753","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3454753","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2024.3454753","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039844226","display_name":"Jun\u2010Hyung Kim","orcid":"https://orcid.org/0000-0003-2231-5209"},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jun-Hyung Kim","raw_affiliation_strings":["Department of Information and Communication Engineering, Chosun University, Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Chosun University, Gwangju, South Korea","institution_ids":["https://openalex.org/I152238500"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049515671","display_name":"Goo\u2010Rak Kwon","orcid":"https://orcid.org/0000-0003-3486-8812"},"institutions":[{"id":"https://openalex.org/I152238500","display_name":"Chosun University","ror":"https://ror.org/01zt9a375","country_code":"KR","type":"education","lineage":["https://openalex.org/I152238500"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Goo-Rak Kwon","raw_affiliation_strings":["Department of Information and Communication Engineering, Chosun University, Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Chosun University, Gwangju, South Korea","institution_ids":["https://openalex.org/I152238500"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5039844226"],"corresponding_institution_ids":["https://openalex.org/I152238500"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.3817,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.84323565,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"12","issue":null,"first_page":"127604","last_page":"127613"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9976000189781189,"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/T14319","display_name":"Currency Recognition and Detection","score":0.9912999868392944,"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/anomaly-detection","display_name":"Anomaly detection","score":0.7432280778884888},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6741790771484375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5588515996932983},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5547762513160706},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4743693768978119},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4330146908760071},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10101991891860962},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.07197272777557373},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.06157636642456055}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7432280778884888},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6741790771484375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5588515996932983},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5547762513160706},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4743693768978119},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4330146908760071},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10101991891860962},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.07197272777557373},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.06157636642456055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3454753","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3454753","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c7378e1b8196404a88a3a65fbb9e8898","is_oa":true,"landing_page_url":"https://doaj.org/article/c7378e1b8196404a88a3a65fbb9e8898","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 127604-127613 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3454753","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3454753","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1966832848","https://openalex.org/W2047643928","https://openalex.org/W2100495367","https://openalex.org/W2133665775","https://openalex.org/W2525778437","https://openalex.org/W2809705434","https://openalex.org/W2896457183","https://openalex.org/W2899280016","https://openalex.org/W2907868778","https://openalex.org/W2908510526","https://openalex.org/W2941813310","https://openalex.org/W2948982773","https://openalex.org/W2963231084","https://openalex.org/W3023371261","https://openalex.org/W3023868590","https://openalex.org/W3085139254","https://openalex.org/W3092704883","https://openalex.org/W3138516171","https://openalex.org/W3147184966","https://openalex.org/W3159481202","https://openalex.org/W3159648608","https://openalex.org/W3160074056","https://openalex.org/W3166166117","https://openalex.org/W3169651898","https://openalex.org/W3173365702","https://openalex.org/W3183588514","https://openalex.org/W3209793239","https://openalex.org/W3212044949","https://openalex.org/W3213836217","https://openalex.org/W4213019189","https://openalex.org/W4214694907","https://openalex.org/W4214893857","https://openalex.org/W4221140561","https://openalex.org/W4283331368","https://openalex.org/W4289792391","https://openalex.org/W4292264335","https://openalex.org/W4312570668","https://openalex.org/W4366208220","https://openalex.org/W4379470918","https://openalex.org/W4385800883","https://openalex.org/W4387225729","https://openalex.org/W4387415072","https://openalex.org/W4396214955","https://openalex.org/W6727690538","https://openalex.org/W6733814495","https://openalex.org/W6752554887","https://openalex.org/W6755207826","https://openalex.org/W6757817989","https://openalex.org/W6777869702","https://openalex.org/W6790530467","https://openalex.org/W6800217721","https://openalex.org/W6804160461","https://openalex.org/W6851800889","https://openalex.org/W6856857450"],"related_works":["https://openalex.org/W2105642232","https://openalex.org/W3197833032","https://openalex.org/W4386081464","https://openalex.org/W3207332793","https://openalex.org/W2499612753","https://openalex.org/W3113278055","https://openalex.org/W2033914206","https://openalex.org/W4285233543","https://openalex.org/W2042327336","https://openalex.org/W4230838436"],"abstract_inverted_index":{"In":[0,35],"the":[1,6,18,25,48,53,98,103,115,124,141],"various":[2],"industrial":[3],"manufacturing":[4],"processes,":[5],"automatic":[7,54],"visual":[8,55],"inspection":[9,56],"system":[10],"is":[11,94,106],"an":[12,63,88,132],"essential":[13],"part":[14],"as":[15,87],"it":[16,86],"reduces":[17],"chances":[19],"of":[20,27,62,131],"delivering":[21],"defective":[22,152],"products":[23,153],"and":[24,29,66,72,102,117,129,161],"cost":[26],"training":[28],"hiring":[30],"experts":[31],"for":[32,52],"manual":[33],"inspection.":[34],"this":[36],"work,":[37],"we":[38],"propose":[39],"a":[40,69,73,78],"new":[41],"unsupervised":[42],"anomaly":[43,110],"detection":[44],"method":[45,60,143],"inspired":[46],"by":[47,154],"masked":[49],"language":[50],"model":[51,83],"system.":[57],"The":[58],"proposed":[59,142],"consists":[61],"image":[64,89,133],"tokenizer":[65,134],"two":[67,125],"subnetworks,":[68],"reconstruction":[70],"subnetwork,":[71],"segmentation":[74,111],"subnetwork.":[75],"We":[76],"adopt":[77],"pre-trained":[79],"self-supervised":[80],"vision":[81],"Transformer":[82],"to":[84,96,108],"use":[85],"tokenizer.":[90],"Our":[91],"first":[92],"subnetwork":[93,105],"trained":[95,107],"predict":[97],"anomaly-free":[99],"patch":[100,119],"tokens":[101],"second":[104],"produce":[109],"results":[112,138],"from":[113],"both":[114],"reconstructed":[116],"input":[118],"tokens.":[120],"During":[121],"training,":[122],"only":[123],"subnetworks":[126],"are":[127,135],"optimized,":[128],"parameters":[130],"frozen.":[136],"Experimental":[137],"show":[139],"that":[140],"exhibits":[144],"better":[145],"performance":[146],"than":[147],"conventional":[148],"methods":[149],"in":[150],"detecting":[151],"achieving":[155],"99.05%":[156],"I-AUROC":[157,163],"on":[158,164],"MVTecAD":[159],"dataset":[160],"94.8%":[162],"BTAD.":[165]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}