{"id":"https://openalex.org/W4379116586","doi":"https://doi.org/10.1109/tim.2023.3280508","title":"OTB-AAE: Semi-Supervised Anomaly Detection on Industrial Images Based on Adversarial Autoencoder With Output-Turn-Back Structure","display_name":"OTB-AAE: Semi-Supervised Anomaly Detection on Industrial Images Based on Adversarial Autoencoder With Output-Turn-Back Structure","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4379116586","doi":"https://doi.org/10.1109/tim.2023.3280508"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2023.3280508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3280508","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/A5048721700","display_name":"Xuezhen LI","orcid":"https://orcid.org/0000-0001-8754-1659"},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuewei Li","raw_affiliation_strings":["School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-8754-1659","affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066405237","display_name":"Junfeng Jing","orcid":"https://orcid.org/0000-0001-6646-3698"},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfeng Jing","raw_affiliation_strings":["School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-6646-3698","affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006384429","display_name":"Junmin Bao","orcid":"https://orcid.org/0000-0001-6381-3963"},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junmin Bao","raw_affiliation_strings":["School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-6381-3963","affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012419850","display_name":"Pengwen Lu","orcid":"https://orcid.org/0000-0001-7445-2593"},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengwen Lu","raw_affiliation_strings":["School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0001-7445-2593","affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102736724","display_name":"Yaohua Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaohua Xie","raw_affiliation_strings":["School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0002-6269-1316","affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I27599042"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ying An","orcid":"https://orcid.org/0000-0003-1289-9677"},"institutions":[{"id":"https://openalex.org/I27599042","display_name":"Xi'an Polytechnic University","ror":"https://ror.org/03442p831","country_code":"CN","type":"education","lineage":["https://openalex.org/I27599042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying An","raw_affiliation_strings":["School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0000-0003-1289-9677","affiliations":[{"raw_affiliation_string":"School of Electronics and Information, Xi&#x2019;an Polytechnic University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I27599042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I27599042"],"apc_list":null,"apc_paid":null,"fwci":2.3794,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.90239639,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"72","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11515","display_name":"Bacillus and Francisella bacterial research","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"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"}},{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9878000020980835,"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/autoencoder","display_name":"Autoencoder","score":0.6668652892112732},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.623066246509552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6203038096427917},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6149289011955261},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.6047016978263855},{"id":"https://openalex.org/keywords/normality","display_name":"Normality","score":0.5521600246429443},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5194703936576843},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5085264444351196},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.43825241923332214},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4190130829811096},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3833998143672943},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32333022356033325},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1479816436767578},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.1195865273475647}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6668652892112732},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.623066246509552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6203038096427917},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6149289011955261},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.6047016978263855},{"id":"https://openalex.org/C2776157432","wikidata":"https://www.wikidata.org/wiki/Q1375683","display_name":"Normality","level":2,"score":0.5521600246429443},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5194703936576843},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5085264444351196},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.43825241923332214},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4190130829811096},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3833998143672943},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32333022356033325},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1479816436767578},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.1195865273475647},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2023.3280508","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2023.3280508","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":[{"display_name":"Reduced inequalities","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G3339146582","display_name":null,"funder_award_id":"62176204","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8780780162","display_name":null,"funder_award_id":"2022GY-066","funder_id":"https://openalex.org/F4320336350","funder_display_name":"Key Research and Development Projects of Shaanxi Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336350","display_name":"Key Research and Development Projects of Shaanxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1514907448","https://openalex.org/W1522301498","https://openalex.org/W1901129140","https://openalex.org/W1959608418","https://openalex.org/W2133665775","https://openalex.org/W2599354622","https://openalex.org/W2739748921","https://openalex.org/W2787947370","https://openalex.org/W2791709739","https://openalex.org/W2888026659","https://openalex.org/W2902758299","https://openalex.org/W2914570111","https://openalex.org/W2944303778","https://openalex.org/W2948982773","https://openalex.org/W2953528808","https://openalex.org/W2953868242","https://openalex.org/W2962808998","https://openalex.org/W2963045681","https://openalex.org/W2963049059","https://openalex.org/W2963420686","https://openalex.org/W2963684088","https://openalex.org/W2981988113","https://openalex.org/W2994615081","https://openalex.org/W2994817145","https://openalex.org/W3007048760","https://openalex.org/W3034314048","https://openalex.org/W3048525077","https://openalex.org/W3091302086","https://openalex.org/W3092704883","https://openalex.org/W3120293860","https://openalex.org/W3147184966","https://openalex.org/W3166166117","https://openalex.org/W3193832355","https://openalex.org/W3204957802","https://openalex.org/W3206269217","https://openalex.org/W3211391700","https://openalex.org/W3213236098","https://openalex.org/W4206450891","https://openalex.org/W4289792391","https://openalex.org/W4292070748","https://openalex.org/W4293568373","https://openalex.org/W4294568686","https://openalex.org/W4317906511","https://openalex.org/W4319299987","https://openalex.org/W4319301146","https://openalex.org/W4320013936","https://openalex.org/W6631190155","https://openalex.org/W6640963894","https://openalex.org/W6685352114","https://openalex.org/W6714590955","https://openalex.org/W6715501732","https://openalex.org/W6741832134","https://openalex.org/W6748495906","https://openalex.org/W6751917112","https://openalex.org/W6780248173"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W3040099731","https://openalex.org/W3017266184","https://openalex.org/W4289406342","https://openalex.org/W2896600774","https://openalex.org/W2918377632","https://openalex.org/W3194885736","https://openalex.org/W3202913553","https://openalex.org/W3046391934","https://openalex.org/W4363671829"],"abstract_inverted_index":{"Due":[0],"to":[1,65,84,87,91,114,127,131,154,188],"the":[2,17,36,42,50,67,88,93,97,101,106,116,119,129,133,143,155,160,169,175,182,194,197],"unbalanced":[3],"proportion":[4],"of":[5,20,38,46,52,70,96,136,142,159,196],"positive":[6,137,146],"(non-anomalous)":[7],"and":[8,41,44,73,105,145,171,200],"negative":[9,47,144],"(anomalous)":[10],"samples":[11,48,147],"obtained":[12],"from":[13],"industrial":[14,24],"data":[15],"collection,":[16],"development":[18],"prospect":[19],"supervised":[21],"algorithms":[22],"in":[23,35,76,150],"field":[25,37],"is":[26,82,123,148],"limited.":[27],"Recently,":[28],"Adversarial":[29],"Autoencoder":[30],"(AAE)":[31],"has":[32],"been":[33],"used":[34],"anomaly":[39,59,184],"detection,":[40],"complexity":[43],"unknown":[45],"increase":[49],"difficulty":[51],"this":[53],"task.":[54],"Here":[55],"we":[56],"propose":[57],"an":[58],"detection":[60,185],"framework":[61],"based":[62],"on":[63,178],"AAE":[64,89,126],"capture":[66,132],"normality":[68,134],"distribution":[69,135,141],"high-dimensional":[71],"images":[72],"identify":[74],"abnormalities":[75],"industry.":[77],"The":[78,139],"Output-Turn-Back":[79],"structure":[80,90],"(OTB)":[81],"proposed":[83,198],"be":[85],"added":[86],"improve":[92,128],"discriminant":[94],"capability":[95],"discriminator.":[98],"In":[99],"particular,":[100],"L1":[102],"loss":[103,110],"function":[104,111],"Structural":[107],"Similarity":[108],"(SSIM)":[109],"are":[112],"combined":[113],"assist":[115],"OTB.":[117],"Then":[118],"Squeeze-and-Excitation":[120],"(SE)":[121],"model":[122,170],"embedded":[124],"into":[125],"ability":[130],"samples.":[138],"characteristic":[140],"different":[149,179],"testing,":[151],"which":[152],"leads":[153],"significant":[156],"reconstruction":[157],"error":[158],"latent":[161],"space":[162],"vector":[163],"encoding,":[164],"indicating":[165],"anomaly.":[166],"We":[167],"test":[168],"compare":[172],"it":[173],"with":[174],"other":[176],"models":[177],"datasets,":[180],"using":[181],"existing":[183],"evaluation":[186],"indexes":[187],"evaluate":[189],"their":[190],"performance.":[191],"Experiments":[192],"prove":[193],"superiority":[195],"method":[199],"its":[201],"unique":[202],"application":[203],"prospect.":[204]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
