{"id":"https://openalex.org/W3194129848","doi":"https://doi.org/10.1109/icip42928.2021.9506433","title":"Anomaly Detection Via Self-Organizing Map","display_name":"Anomaly Detection Via Self-Organizing Map","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3194129848","doi":"https://doi.org/10.1109/icip42928.2021.9506433","mag":"3194129848"},"language":"en","primary_location":{"id":"doi:10.1109/icip42928.2021.9506433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100369062","display_name":"Ning Li","orcid":"https://orcid.org/0000-0002-8906-4849"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Li","raw_affiliation_strings":["Xi’an Jiaotong University,School of Software Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,School of Software Engineering","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061826902","display_name":"Kaitao Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaitao Jiang","raw_affiliation_strings":["Xi’an Jiaotong University,Faculty of Electronic and Information Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,Faculty of Electronic and Information Engineering","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008366979","display_name":"Zhiheng Ma","orcid":"https://orcid.org/0000-0002-0034-2065"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Ma","raw_affiliation_strings":["Xi’an Jiaotong University,Faculty of Electronic and Information Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,Faculty of Electronic and Information Engineering","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040886197","display_name":"Xing Wei","orcid":"https://orcid.org/0000-0002-5025-3941"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Wei","raw_affiliation_strings":["Xi’an Jiaotong University,School of Software Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,School of Software Engineering","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026880795","display_name":"Xiaopeng Hong","orcid":"https://orcid.org/0000-0002-0611-0636"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaopeng Hong","raw_affiliation_strings":["Xi’an Jiaotong University,Faculty of Electronic and Information Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,Faculty of Electronic and Information Engineering","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100687952","display_name":"Yihong Gong","orcid":"https://orcid.org/0000-0002-1793-5836"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihong Gong","raw_affiliation_strings":["Xi’an Jiaotong University,School of Software Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi’an Jiaotong University,School of Software Engineering","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"974","last_page":"978"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9767000079154968,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9703999757766724,"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":0.8448786735534668},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7152439951896667},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6793461441993713},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6165508031845093},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5548238158226013},{"id":"https://openalex.org/keywords/self-organizing-map","display_name":"Self-organizing map","score":0.5441495180130005},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5113334059715271},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.47589266300201416},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46497678756713867},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.45285066962242126},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.44501224160194397},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3480517566204071},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.21869447827339172},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09377637505531311},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06324610114097595},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.05527427792549133}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8448786735534668},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7152439951896667},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6793461441993713},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6165508031845093},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5548238158226013},{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.5441495180130005},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5113334059715271},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.47589266300201416},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46497678756713867},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.45285066962242126},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.44501224160194397},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3480517566204071},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.21869447827339172},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09377637505531311},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06324610114097595},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.05527427792549133},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip42928.2021.9506433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1540596182","https://openalex.org/W1959608418","https://openalex.org/W2079810998","https://openalex.org/W2108598243","https://openalex.org/W2430196102","https://openalex.org/W2914570111","https://openalex.org/W2948982773","https://openalex.org/W2949982377","https://openalex.org/W2963045681","https://openalex.org/W2963049059","https://openalex.org/W2964137095","https://openalex.org/W2987228832","https://openalex.org/W3008638899","https://openalex.org/W3013379031","https://openalex.org/W3023868590","https://openalex.org/W3034314048","https://openalex.org/W3034648032","https://openalex.org/W3034997474","https://openalex.org/W3048815401","https://openalex.org/W3091518487","https://openalex.org/W3091561623","https://openalex.org/W3092862085","https://openalex.org/W3106848223","https://openalex.org/W3114010851","https://openalex.org/W3118895125","https://openalex.org/W3128445833","https://openalex.org/W3147184966","https://openalex.org/W3151160911","https://openalex.org/W3160366495","https://openalex.org/W6632267817","https://openalex.org/W6640963894","https://openalex.org/W6713132643","https://openalex.org/W6717870063","https://openalex.org/W6751917112","https://openalex.org/W6753123669","https://openalex.org/W6775204614","https://openalex.org/W6777869702","https://openalex.org/W6779227824","https://openalex.org/W6779937703","https://openalex.org/W6781627986","https://openalex.org/W6782561540","https://openalex.org/W6783738328","https://openalex.org/W6785596320","https://openalex.org/W6786114270","https://openalex.org/W6790530467"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Anomaly":[0,83],"detection":[1,17,71,104],"plays":[2],"a":[3,54,58,67],"key":[4],"role":[5],"in":[6,57],"industrial":[7],"manufacturing":[8],"for":[9,15,39,82],"product":[10],"quality":[11],"control.":[12],"Traditional":[13],"methods":[14,25],"anomaly":[16,70,103],"are":[18,31,45],"rule-based":[19],"with":[20],"limited":[21],"generalization":[22],"ability.":[23],"Recent":[24],"based":[26,73,93],"on":[27,74,94,101,107],"supervised":[28,60],"deep":[29,55],"learning":[30],"more":[32],"powerful":[33],"but":[34],"require":[35],"large-scale":[36],"annotated":[37],"datasets":[38],"training.":[40],"In":[41,62],"practice,":[42],"abnormal":[43],"products":[44],"rare":[46],"thus":[47],"it":[48],"is":[49],"very":[50],"difficult":[51],"to":[52],"train":[53],"model":[56],"fully":[59],"way.":[61],"this":[63],"paper,":[64],"we":[65],"propose":[66],"novel":[68],"unsupervised":[69,102],"approach":[72],"Self-organizing":[75,80],"Map":[76,81],"(SOM).":[77],"Our":[78],"method,":[79],"Detection":[84],"(SOMAD)":[85],"maintains":[86],"normal":[87],"characteristics":[88],"by":[89],"using":[90],"topological":[91],"memory":[92],"multi-scale":[95],"features.":[96],"SOMAD":[97],"achieves":[98],"state-of-the-art":[99],"performance":[100],"and":[105],"localization":[106],"the":[108],"MVTec":[109],"dataset.":[110]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}