{"id":"https://openalex.org/W4318831100","doi":"https://doi.org/10.1109/tii.2023.3241579","title":"Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization","display_name":"Collaborative Discrepancy Optimization for Reliable Image Anomaly Localization","publication_year":2023,"publication_date":"2023-02-01","ids":{"openalex":"https://openalex.org/W4318831100","doi":"https://doi.org/10.1109/tii.2023.3241579"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2023.3241579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2023.3241579","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2302.08769","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044965902","display_name":"Yunkang Cao","orcid":"https://orcid.org/0000-0001-7619-6618"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunkang Cao","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-7619-6618","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018803784","display_name":"Xiaohao Xu","orcid":"https://orcid.org/0000-0002-6750-9704"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohao Xu","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053242272","display_name":"Zhaoge Liu","orcid":"https://orcid.org/0000-0002-0350-9035"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoge Liu","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-0350-9035","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062049138","display_name":"Weiming Shen","orcid":"https://orcid.org/0000-0001-5204-7992"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiming Shen","raw_affiliation_strings":["State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-5204-7992","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I47720641"],"apc_list":null,"apc_paid":null,"fwci":15.7997,"has_fulltext":true,"cited_by_count":121,"citation_normalized_percentile":{"value":0.99409821,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"19","issue":"11","first_page":"10674","last_page":"10683"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9925000071525574,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9872000217437744,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5208390355110168},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4513480067253113},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4260942041873932},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4214153289794922},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33350831270217896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5208390355110168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4513480067253113},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4260942041873932},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4214153289794922},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33350831270217896}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tii.2023.3241579","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2023.3241579","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"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 Industrial Informatics","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2302.08769","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.08769","pdf_url":"https://arxiv.org/pdf/2302.08769","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2302.08769","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2302.08769","pdf_url":"https://arxiv.org/pdf/2302.08769","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.41999998688697815,"display_name":"Industry, innovation and infrastructure"}],"awards":[{"id":"https://openalex.org/G580016197","display_name":null,"funder_award_id":"2021GCRC058","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4318831100.pdf"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2884561390","https://openalex.org/W2908510526","https://openalex.org/W2964137095","https://openalex.org/W2987228832","https://openalex.org/W2994615081","https://openalex.org/W3014641072","https://openalex.org/W3034314048","https://openalex.org/W3092704883","https://openalex.org/W3101017490","https://openalex.org/W3106848223","https://openalex.org/W3109771882","https://openalex.org/W3113008830","https://openalex.org/W3118600296","https://openalex.org/W3118895125","https://openalex.org/W3147184966","https://openalex.org/W3169077988","https://openalex.org/W3175716777","https://openalex.org/W3177716034","https://openalex.org/W3183588514","https://openalex.org/W3208797540","https://openalex.org/W4206551889","https://openalex.org/W4212919149","https://openalex.org/W4213270700","https://openalex.org/W4214694907","https://openalex.org/W4221140401","https://openalex.org/W4224999518","https://openalex.org/W4239072543","https://openalex.org/W4281287416","https://openalex.org/W4312772600","https://openalex.org/W4319301058","https://openalex.org/W4376626035","https://openalex.org/W6757817989","https://openalex.org/W6802573413"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Most":[0],"unsupervised":[1],"image":[2],"anomaly":[3,123],"localization":[4,68,124],"methods":[5],"suffer":[6],"from":[7],"overgeneralization":[8,119],"because":[9],"of":[10,15,41,81,141],"the":[11,25,39,62,67,71,74,77,103,118,139,142],"high":[12],"generalization":[13],"abilities":[14],"convolutional":[16],"neural":[17],"networks,":[18],"leading":[19],"to":[20,30,60],"unreliable":[21],"predictions.":[22],"To":[23],"mitigate":[24],"overgeneralization,":[26],"this":[27],"article":[28],"proposes":[29],"collaboratively":[31],"optimize":[32,61],"normal":[33,82,96],"and":[34,55,73,83,91,97,102,111,120],"abnormal":[35,84,98],"feature":[36],"distributions":[37,79],"with":[38,126],"assistance":[40],"synthetic":[42],"anomalies,":[43],"namely":[44],"collaborative":[45],"discrepancy":[46,78],"optimization":[47,53,58],"(CDO).":[48],"CDO":[49,115],"introduces":[50],"a":[51,88,92],"margin":[52,72,90],"module":[54,59],"an":[56],"overlap":[57,75,94],"two":[63],"key":[64],"factors":[65],"determining":[66],"performance,":[69],"i.e.,":[70],"between":[76,95],"(DDs)":[80],"samples.":[85],"With":[86],"CDO,":[87],"large":[89],"small":[93],"DDs":[99],"are":[100],"obtained,":[101],"prediction":[104],"reliability":[105],"is":[106],"boosted.":[107],"Experiments":[108],"on":[109],"MVTec2D":[110],"MVTec3D":[112],"show":[113],"that":[114],"effectively":[116],"mitigates":[117],"achieves":[121],"great":[122],"performance":[125],"real-time":[127],"computation":[128],"efficiency.":[129],"A":[130],"real-world":[131],"automotive":[132],"plastic":[133],"parts":[134],"inspection":[135],"application":[136],"further":[137],"demonstrates":[138],"capability":[140],"proposed":[143],"CDO.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":26},{"year":2025,"cited_by_count":57},{"year":2024,"cited_by_count":32},{"year":2023,"cited_by_count":6}],"updated_date":"2026-08-02T14:50:37.381335","created_date":"2025-10-10T00:00:00"}