{"id":"https://openalex.org/W3193992273","doi":"https://doi.org/10.1109/tim.2021.3107586","title":"Unsupervised Anomaly Segmentation Via Multilevel Image Reconstruction and Adaptive Attention-Level Transition","display_name":"Unsupervised Anomaly Segmentation Via Multilevel Image Reconstruction and Adaptive Attention-Level Transition","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3193992273","doi":"https://doi.org/10.1109/tim.2021.3107586","mag":"3193992273"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2021.3107586","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3107586","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5052970855","display_name":"Yi Yan","orcid":"https://orcid.org/0000-0002-8579-4211"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Yan","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0002-8579-4211","affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100439508","display_name":"Deming Wang","orcid":"https://orcid.org/0000-0003-3486-4176"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Deming Wang","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0003-3486-4176","affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059751345","display_name":"Guangliang Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangliang Zhou","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-7845-7068","affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073789459","display_name":"Qijun Chen","orcid":"https://orcid.org/0000-0001-5644-1188"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qijun Chen","raw_affiliation_strings":["College of Electronics and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-5644-1188","affiliations":[{"raw_affiliation_string":"College of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":5.8688,"has_fulltext":false,"cited_by_count":59,"citation_normalized_percentile":{"value":0.96709955,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T11512","display_name":"Anomaly Detection Techniques and Applications","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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9969000220298767,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.76475989818573},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6882824301719666},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6262355446815491},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5601561069488525},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5232314467430115},{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.5117583274841309},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4791147708892822},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4749488830566406},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.4739684760570526},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4639750123023987},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19467458128929138}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.76475989818573},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6882824301719666},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6262355446815491},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5601561069488525},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5232314467430115},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.5117583274841309},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4791147708892822},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4749488830566406},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.4739684760570526},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4639750123023987},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19467458128929138},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2021.3107586","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3107586","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2581980031","display_name":null,"funder_award_id":"62073245","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5565712806","display_name":null,"funder_award_id":"61733013","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":70,"referenced_works":["https://openalex.org/W343636949","https://openalex.org/W582134693","https://openalex.org/W1686810756","https://openalex.org/W1955055330","https://openalex.org/W1959608418","https://openalex.org/W1970088130","https://openalex.org/W2099471712","https://openalex.org/W2117539524","https://openalex.org/W2133665775","https://openalex.org/W2194775991","https://openalex.org/W2331128040","https://openalex.org/W2476548250","https://openalex.org/W2545601451","https://openalex.org/W2599354622","https://openalex.org/W2600383743","https://openalex.org/W2783748519","https://openalex.org/W2791709739","https://openalex.org/W2803697594","https://openalex.org/W2807007689","https://openalex.org/W2809705434","https://openalex.org/W2914570111","https://openalex.org/W2947805333","https://openalex.org/W2948982773","https://openalex.org/W2950517871","https://openalex.org/W2962785568","https://openalex.org/W2962793481","https://openalex.org/W2963045681","https://openalex.org/W2963049059","https://openalex.org/W2963073614","https://openalex.org/W2963174698","https://openalex.org/W2963800363","https://openalex.org/W2964059111","https://openalex.org/W2964149421","https://openalex.org/W2982324952","https://openalex.org/W2982519139","https://openalex.org/W2982763192","https://openalex.org/W2983315964","https://openalex.org/W2996904338","https://openalex.org/W2999653953","https://openalex.org/W3023868590","https://openalex.org/W3034314048","https://openalex.org/W3034419329","https://openalex.org/W3034648032","https://openalex.org/W3035426499","https://openalex.org/W3092704883","https://openalex.org/W3101017490","https://openalex.org/W3102544523","https://openalex.org/W3105515746","https://openalex.org/W3105939760","https://openalex.org/W3106848223","https://openalex.org/W3109715690","https://openalex.org/W3109771882","https://openalex.org/W3128803071","https://openalex.org/W4287869122","https://openalex.org/W4297800839","https://openalex.org/W4320013936","https://openalex.org/W6617145748","https://openalex.org/W6637373629","https://openalex.org/W6640963894","https://openalex.org/W6692550842","https://openalex.org/W6702130928","https://openalex.org/W6735443497","https://openalex.org/W6751494907","https://openalex.org/W6751831877","https://openalex.org/W6751917112","https://openalex.org/W6771530079","https://openalex.org/W6775494149","https://openalex.org/W6777869702","https://openalex.org/W6779937703","https://openalex.org/W6785346639"],"related_works":["https://openalex.org/W2062399876","https://openalex.org/W2607795551","https://openalex.org/W3155117723","https://openalex.org/W1991429770","https://openalex.org/W1983892167","https://openalex.org/W2281134365","https://openalex.org/W4310746709","https://openalex.org/W4306309518","https://openalex.org/W4385574037","https://openalex.org/W4212888438"],"abstract_inverted_index":{"In":[0],"product":[1],"inspection":[2],"scenarios,":[3],"the":[4,42,71,76,94,101,114,120,125,153,163,168,176,199,206,216],"objects":[5],"have":[6],"different":[7,12,53,85,157,212],"characteristics":[8],"of":[9,78,127,167],"textures":[10],"and":[11,23,62,131,145,190,203,214],"potential":[13],"anomalies.":[14,81],"Still,":[15],"traditional":[16],"methods":[17],"cannot":[18],"precisely":[19],"segment":[20],"structural":[21],"anomalies":[22],"achieve":[24],"optimal":[25],"performance":[26,116],"on":[27,93,100,198],"all":[28],"object":[29],"categories.":[30],"This":[31,149],"article":[32],"introduces":[33],"a":[34,140],"flexible":[35],"multilevel":[36],"image":[37,183,191],"reconstruction":[38,60,73,102,129,144,177],"(MLIR)":[39],"framework":[40],"for":[41,88,143,156],"unsupervised":[43],"anomaly":[44,146],"segmentation":[45],"task.":[46],"The":[47],"MLIR":[48],"integrates":[49],"multiple":[50,59],"generators":[51,90],"with":[52,84],"downsampling":[54],"ratios":[55],"to":[56,69,104,119,136,211],"serve":[57],"as":[58,181],"levels":[61,130],"leverage":[63],"an":[64,106,182],"adjustable":[65],"perceptual":[66],"similarity":[67],"measurement":[68,133],"obtain":[70],"featurewise":[72],"errors,":[74],"overcoming":[75],"challenge":[77],"detecting":[79],"multiscale":[80],"Leveraging":[82],"embeddings":[83],"receptive":[86],"fields":[87],"reconstruction,":[89],"perform":[91],"differently":[92],"same":[95],"target.":[96],"Therefore,":[97],"we":[98,160],"depend":[99],"uncertainty":[103],"propose":[105,161],"adaptive":[107],"attention-level":[108],"transition":[109],"(ALT)":[110],"strategy":[111,150],"that":[112,175,205],"optimizes":[113],"detection":[115,147],"automatically":[117],"according":[118],"target's":[121],"category.":[122],"ALT":[123],"adjusts":[124],"weights":[126],"both":[128],"feature":[132,188],"scales":[134],"simultaneously":[135],"utilize":[137],"features":[138],"at":[139],"consistent":[141],"level":[142],"(AD).":[148],"remarkably":[151],"improves":[152,187],"system's":[154],"adaptivity":[155],"applications.":[158],"Moreover,":[159],"reducing":[162],"signal-to-noise":[164],"ratio":[165],"(SNR)":[166],"images":[169],"by":[170],"adding":[171],"pepper":[172],"noise":[173],"so":[174],"process":[178],"is":[179],"framed":[180],"denoising":[184],"task,":[185],"which":[186],"extraction":[189],"restoration":[192],"robustness.":[193],"We":[194],"conduct":[195],"extensive":[196],"experiments":[197],"MVTec":[200],"AD":[201],"dataset":[202],"demonstrate":[204],"proposed":[207],"method":[208],"performs":[209],"satisfactorily":[210],"categories":[213],"achieves":[215],"state-of-the-art":[217],"(SOTA)":[218],"performance.":[219]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":14},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
