{"id":"https://openalex.org/W4312763576","doi":"https://doi.org/10.1109/tai.2022.3227142","title":"Learning Multiresolution Features for Unsupervised Anomaly Localization on Industrial Textured Surfaces","display_name":"Learning Multiresolution Features for Unsupervised Anomaly Localization on Industrial Textured Surfaces","publication_year":2022,"publication_date":"2022-12-06","ids":{"openalex":"https://openalex.org/W4312763576","doi":"https://doi.org/10.1109/tai.2022.3227142"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2022.3227142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2022.3227142","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Artificial Intelligence","raw_type":"journal-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/A5082921939","display_name":"Xian Tao","orcid":"https://orcid.org/0000-0001-5834-5181"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xian Tao","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","Binzhou Institute of Technology, Binzhou, China","CAS Engineering Laboratory for Intelligent Industrial Vision, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]},{"raw_affiliation_string":"Binzhou Institute of Technology, Binzhou, China","institution_ids":[]},{"raw_affiliation_string":"CAS Engineering Laboratory for Intelligent Industrial Vision, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026518190","display_name":"Shaohua Yan","orcid":"https://orcid.org/0000-0002-2575-1447"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaohua Yan","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054218873","display_name":"Xinyi Gong","orcid":"https://orcid.org/0000-0002-6515-2836"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]},{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyi Gong","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences, Beijing, China","School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210094879","https://openalex.org/I19820366"]},{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210100255","https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034677436","display_name":"Chandranath Adak","orcid":"https://orcid.org/0000-0002-9085-2770"},"institutions":[{"id":"https://openalex.org/I132153292","display_name":"Indian Institute of Technology Patna","ror":"https://ror.org/01ft5vz71","country_code":"IN","type":"education","lineage":["https://openalex.org/I132153292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chandranath Adak","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology Patna, Bihar, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology Patna, Bihar, India","institution_ids":["https://openalex.org/I132153292"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5082921939"],"corresponding_institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210094879","https://openalex.org/I4210100255","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":1.2174,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.82334341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"5","issue":"1","first_page":"127","last_page":"139"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9771999716758728,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.972000002861023,"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/autoencoder","display_name":"Autoencoder","score":0.8111981153488159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7704099416732788},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7037209272384644},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6509369611740112},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6224117875099182},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5977975130081177},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.5913487672805786},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5392019152641296},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.45274221897125244},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.41012558341026306},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4052659869194031},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.39604490995407104},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.07165047526359558}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8111981153488159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7704099416732788},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7037209272384644},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6509369611740112},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6224117875099182},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5977975130081177},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.5913487672805786},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5392019152641296},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.45274221897125244},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.41012558341026306},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4052659869194031},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39604490995407104},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.07165047526359558},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2022.3227142","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2022.3227142","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5899999737739563,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G462741468","display_name":null,"funder_award_id":"62066004","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":73,"referenced_works":["https://openalex.org/W1635340334","https://openalex.org/W1686810756","https://openalex.org/W1884984464","https://openalex.org/W2117539524","https://openalex.org/W2519371957","https://openalex.org/W2550866408","https://openalex.org/W2599354622","https://openalex.org/W2616247523","https://openalex.org/W2752782242","https://openalex.org/W2784032999","https://openalex.org/W2791709739","https://openalex.org/W2809705434","https://openalex.org/W2831321715","https://openalex.org/W2907868778","https://openalex.org/W2923486253","https://openalex.org/W2925274914","https://openalex.org/W2963045681","https://openalex.org/W2984212836","https://openalex.org/W2984463702","https://openalex.org/W2998008435","https://openalex.org/W3003982163","https://openalex.org/W3023868590","https://openalex.org/W3027429685","https://openalex.org/W3034314048","https://openalex.org/W3034648032","https://openalex.org/W3035102456","https://openalex.org/W3048310130","https://openalex.org/W3048815401","https://openalex.org/W3088594381","https://openalex.org/W3089028909","https://openalex.org/W3092704883","https://openalex.org/W3101017490","https://openalex.org/W3102564565","https://openalex.org/W3104156061","https://openalex.org/W3106848223","https://openalex.org/W3109715690","https://openalex.org/W3109771882","https://openalex.org/W3118600296","https://openalex.org/W3121084473","https://openalex.org/W3121899827","https://openalex.org/W3122380385","https://openalex.org/W3126552953","https://openalex.org/W3127080232","https://openalex.org/W3129082918","https://openalex.org/W3129166376","https://openalex.org/W3132936317","https://openalex.org/W3136100689","https://openalex.org/W3145357517","https://openalex.org/W3147184966","https://openalex.org/W3154872378","https://openalex.org/W3159922383","https://openalex.org/W3160074056","https://openalex.org/W3166166117","https://openalex.org/W3169077988","https://openalex.org/W3169770973","https://openalex.org/W3173538657","https://openalex.org/W3215156797","https://openalex.org/W4285114415","https://openalex.org/W4285293775","https://openalex.org/W4289527763","https://openalex.org/W4289792391","https://openalex.org/W4301039631","https://openalex.org/W4365395996","https://openalex.org/W6637373629","https://openalex.org/W6757817989","https://openalex.org/W6771530079","https://openalex.org/W6777869702","https://openalex.org/W6781627986","https://openalex.org/W6789477242","https://openalex.org/W6790530467","https://openalex.org/W6792079315","https://openalex.org/W6792889187","https://openalex.org/W6845169375"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W3186512740","https://openalex.org/W3194885736","https://openalex.org/W3046391934","https://openalex.org/W4363671829","https://openalex.org/W4285233543","https://openalex.org/W2806873178","https://openalex.org/W2770818364","https://openalex.org/W2965146396","https://openalex.org/W4230838436"],"abstract_inverted_index":{"In":[0,59],"industrial":[1,161],"quality":[2],"assessment,":[3],"monitoring":[4],"whether":[5],"the":[6,87,91,95,104,132,137,148,156,159,171],"textured":[7],"product":[8],"contains":[9],"defects":[10,73],"is":[11,40,67,82,129,168],"a":[12,17,62,125],"critical":[13],"step.":[14],"Compared":[15],"to":[16,26,42,69,85,103,134,158],"large":[18],"number":[19],"of":[20,98,121,151],"defect-free":[21],"images":[22,56],"that":[23,52],"are":[24,30,101],"easy":[25],"obtain,":[27],"anomaly":[28],"samples":[29],"limited":[31],"and":[32,37,46,164],"vary":[33],"randomly":[34],"in":[35,74,114,131],"size":[36],"type.":[38],"It":[39],"challenging":[41],"develop":[43],"an":[44,75],"automatic":[45],"accurate":[47],"texture":[48,72,149,162],"defect":[49],"localization":[50],"system":[51],"only":[53],"uses":[54],"normal":[55],"for":[57,118],"training.":[58],"this":[60],"article,":[61],"multiresolution":[63],"feature":[64],"learning":[65],"network":[66],"proposed":[68,141],"detect":[70],"various":[71,99,122],"unsupervised":[76],"manner.":[77],"A":[78],"robust":[79],"pretrained":[80],"model":[81],"first":[83],"employed":[84],"extract":[86],"perceptual":[88,96],"features":[89,97],"from":[90],"input":[92],"image,":[93],"then":[94],"layers":[100],"fed":[102],"corresponding":[105],"multiscale":[106],"autoencoder":[107],"framework.":[108],"This":[109],"hierarchical":[110],"alignment":[111],"strategy":[112],"aids":[113],"receiving":[115],"multilevel":[116],"information":[117],"locating":[119],"anomalies":[120],"sizes.":[123],"Moreover,":[124],"residual":[126],"attention":[127],"module":[128],"embedded":[130],"architecture":[133],"further":[135],"improve":[136],"detection":[138,166],"performance.":[139],"Our":[140],"method":[142],"has":[143],"achieved":[144],"state-of-the-art":[145],"performance":[146],"on":[147],"dataset":[150],"MVTecAD.":[152],"We":[153],"also":[154],"extended":[155],"experiment":[157],"real":[160],"datasets,":[163],"its":[165],"result":[167],"better":[169],"than":[170],"major":[172],"existing":[173],"advanced":[174],"techniques.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}
