{"id":"https://openalex.org/W3092212698","doi":"https://doi.org/10.1109/etfa46521.2020.9212172","title":"Automated Optical Inspection Using Anomaly Detection and Unsupervised Defect Clustering","display_name":"Automated Optical Inspection Using Anomaly Detection and Unsupervised Defect Clustering","publication_year":2020,"publication_date":"2020-09-01","ids":{"openalex":"https://openalex.org/W3092212698","doi":"https://doi.org/10.1109/etfa46521.2020.9212172","mag":"3092212698"},"language":"en","primary_location":{"id":"doi:10.1109/etfa46521.2020.9212172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa46521.2020.9212172","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","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/A5003801733","display_name":"Jan Lehr","orcid":"https://orcid.org/0000-0002-3392-0108"},"institutions":[{"id":"https://openalex.org/I4210148503","display_name":"Fraunhofer Institute for Production Systems and Design Technology","ror":"https://ror.org/045eg9c12","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210148503","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jan Lehr","raw_affiliation_strings":["Division of Automation Technology, Fraunhofer IPK, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Automation Technology, Fraunhofer IPK, Berlin, Germany","institution_ids":["https://openalex.org/I4210148503"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038107917","display_name":"Alik Sargsyan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Alik Sargsyan","raw_affiliation_strings":["Ngene LLC, Yerevan, Armenia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ngene LLC, Yerevan, Armenia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001444359","display_name":"Martin Pape","orcid":"https://orcid.org/0000-0001-7351-9813"},"institutions":[{"id":"https://openalex.org/I4210148503","display_name":"Fraunhofer Institute for Production Systems and Design Technology","ror":"https://ror.org/045eg9c12","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210148503","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Pape","raw_affiliation_strings":["Division of Automation Technology, Fraunhofer IPK, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Automation Technology, Fraunhofer IPK, Berlin, Germany","institution_ids":["https://openalex.org/I4210148503"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091141389","display_name":"Jan Philipps","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148503","display_name":"Fraunhofer Institute for Production Systems and Design Technology","ror":"https://ror.org/045eg9c12","country_code":"DE","type":"facility","lineage":["https://openalex.org/I4210148503","https://openalex.org/I4923324"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jan Philipps","raw_affiliation_strings":["Division of Automation Technology, Fraunhofer IPK, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Automation Technology, Fraunhofer IPK, Berlin, Germany","institution_ids":["https://openalex.org/I4210148503"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065074078","display_name":"J\u00f6rg Kr\u00fcger","orcid":"https://orcid.org/0000-0001-5138-0793"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Jorg Kruger","raw_affiliation_strings":["Division of Industrial Automation Technology, Technical University Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Division of Industrial Automation Technology, Technical University Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1235","last_page":"1238"},"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":1.0,"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":1.0,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9937999844551086,"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"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9912999868392944,"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":0.7861618995666504},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.719715416431427},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6879183650016785},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.632978081703186},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.5726672410964966},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5708907246589661},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.558167040348053},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4877181947231293},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45953914523124695},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38182559609413147}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7861618995666504},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.719715416431427},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6879183650016785},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.632978081703186},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.5726672410964966},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5708907246589661},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.558167040348053},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4877181947231293},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45953914523124695},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38182559609413147},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/etfa46521.2020.9212172","is_oa":false,"landing_page_url":"https://doi.org/10.1109/etfa46521.2020.9212172","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-614531","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-614531.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer IPK","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/409402","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/409402","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"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":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2108598243","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2332845971","https://openalex.org/W2752782242","https://openalex.org/W2809705434","https://openalex.org/W2891040920","https://openalex.org/W2920946673","https://openalex.org/W2948982773","https://openalex.org/W2963420686","https://openalex.org/W2979654309","https://openalex.org/W2982781781","https://openalex.org/W3009635072","https://openalex.org/W3101017490","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W3196155444","https://openalex.org/W2076520961","https://openalex.org/W4285233543","https://openalex.org/W3209574120","https://openalex.org/W4285260836","https://openalex.org/W3046775127","https://openalex.org/W3123344745","https://openalex.org/W4367692580","https://openalex.org/W3208099188","https://openalex.org/W4306321456"],"abstract_inverted_index":{"Neural":[0],"networks":[1,20],"have":[2],"proven":[3],"to":[4,17,35,189,213,225],"be":[5],"extraordinarily":[6],"successful":[7],"in":[8,48,100,106,201],"many":[9],"computer":[10,50],"vision":[11,51],"applications.":[12],"But":[13],"the":[14,41,69,72,88,97,101,171,176,202,206,215],"approaches":[15,177],"used":[16],"train":[18],"neural":[19],"require":[21],"large":[22],"datasets":[23],"of":[24,32,43,90,143,150,170,185,205],"annotated":[25],"images,":[26],"which":[27,195],"requires":[28],"a":[29,56,94,127,136,165,219],"solid":[30],"amount":[31],"human":[33],"time":[34],"prepare":[36],"those":[37],"datasets.":[38],"To":[39],"facilitate":[40],"adoption":[42],"machine":[44],"learning":[45,59],"based":[46,86],"technologies":[47],"industrial":[49,133],"applications,":[52],"this":[53,186],"paper":[54,125],"presents":[55,126],"two-step":[57],"unsupervised":[58,107],"approach":[60],"for":[61,160,164,178,229],"anomaly":[62,83],"detection":[63],"with":[64,116,135],"further":[65],"defect":[66],"clusterization.":[67],"In":[68,93],"first":[70,102,128],"stage,":[71,96],"defects":[73,151,191],"are":[74,79,104,158,174],"not":[75],"explicitly":[76],"learned,":[77],"but":[78],"interpreted":[80],"as":[81],"an":[82,161],"or":[84,121],"novelty":[85],"on":[87,155,192],"dataset":[89,130],"defect-free":[91,232],"samples.":[92],"second":[95],"anomalies":[98],"detected":[99],"stage":[103],"clustered":[105],"manner":[108],"and":[109,145,152,211,231],"classified":[110],"into":[111],"meaningful":[112],"categories":[113],"by":[114],"experts":[115],"process":[117],"knowledge":[118],"(e.g.":[119],"critical":[120],"non-critical":[122],"defect).":[123],"This":[124],"small":[129],"containing":[131],"one":[132],"object":[134,140],"complex":[137],"shape.":[138],"The":[139,183],"is":[141,146,188],"made":[142],"aluminium":[144],"shown":[147],"both":[148],"free":[149],"defective.":[153],"Based":[154],"this,":[156],"recommendations":[157],"given":[159],"acquisition":[162],"setup":[163],"large,":[166],"extensive":[167],"dataset.":[168],"Most":[169],"existing":[172],"papers":[173],"studying":[175],"uniform":[179,199],"surface":[180],"(texture)":[181],"inspection.":[182],"specifics":[184],"research":[187],"identify":[190],"rigid":[193],"bodies,":[194],"exhibit":[196],"highly":[197],"non":[198],"texture":[200],"image.":[203],"State":[204],"art":[207],"methods":[208],"were":[209],"evaluated":[210],"improved":[212],"increase":[214],"classification":[216],"accuracy.":[217],"With":[218],"fine-tuned":[220],"ResNet-18":[221],"it":[222],"was":[223],"possible":[224],"achieve":[226],"100%":[227],"accuracy":[228],"defective":[230],"images.":[233]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
