{"id":"https://openalex.org/W7087407809","doi":"https://doi.org/10.18420/inf2025_116","title":"How Similar is Too Different? A DINOv2-Based Defect Detection Method","display_name":"How Similar is Too Different? A DINOv2-Based Defect Detection Method","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7087407809","doi":"https://doi.org/10.18420/inf2025_116"},"language":"en","primary_location":{"id":"doi:10.18420/inf2025_116","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2025_116","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.18420/inf2025_116","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Flores Jarrin, Juan F.","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Flores Jarrin, Juan F.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Sturm, Fabian","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sturm, Fabian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Menz, Benjamin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Menz, Benjamin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Bocklet, Tobias","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bocklet, Tobias","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.64246362,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T12298","display_name":"Phytochemicals and Medicinal Plants","score":0.2944999933242798,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T12298","display_name":"Phytochemicals and Medicinal Plants","score":0.2944999933242798,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"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/T10308","display_name":"Systemic Lupus Erythematosus Research","score":0.1712999939918518,"subfield":{"id":"https://openalex.org/subfields/2745","display_name":"Rheumatology"},"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/T11532","display_name":"Chemokine receptors and signaling","score":0.07329999655485153,"subfield":{"id":"https://openalex.org/subfields/2730","display_name":"Oncology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5396999716758728},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5134999752044678},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.48820000886917114},{"id":"https://openalex.org/keywords/cosine-similarity","display_name":"Cosine similarity","score":0.48159998655319214},{"id":"https://openalex.org/keywords/simplicity","display_name":"Simplicity","score":0.4724999964237213},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4683000147342682},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4569999873638153},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45350000262260437}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6963000297546387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6697999835014343},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5501000285148621},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5396999716758728},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5134999752044678},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.48820000886917114},{"id":"https://openalex.org/C2780762811","wikidata":"https://www.wikidata.org/wiki/Q1784941","display_name":"Cosine similarity","level":3,"score":0.48159998655319214},{"id":"https://openalex.org/C2776372474","wikidata":"https://www.wikidata.org/wiki/Q508291","display_name":"Simplicity","level":2,"score":0.4724999964237213},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4683000147342682},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4569999873638153},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45350000262260437},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.42570000886917114},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.415800005197525},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.3671000003814697},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3578000068664551},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3571000099182129},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.34929999709129333},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.30329999327659607},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30230000615119934},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.28769999742507935},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2653000056743622},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.26429998874664307},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.25769999623298645},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.25130000710487366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18420/inf2025_116","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2025_116","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.18420/inf2025_116","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2025_116","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.43426164984703064},{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.4001988470554352}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Problem-free":[0],"defect":[1,20],"detection":[2,21],"with":[3,92],"neural":[4],"networks":[5],"is":[6,25],"still":[7],"a":[8,48,132],"challenge":[9],"in":[10,15,35],"flexible":[11,36],"industrial":[12,37,136],"environments,":[13],"especially":[14],"contract":[16],"manufacturing.":[17],"A":[18],"training-free":[19],"system":[22],"using":[23],"DINOv2":[24],"proposed":[26],"to":[27,56],"address":[28],"these":[29],"challenges":[30],"of":[31,98,105,116],"resource-intensive":[32],"model":[33,148],"training":[34],"environments.":[38],"The":[39,111,125],"method":[40],"leverages":[41],"patch-level":[42],"embeddings,":[43],"where":[44],"each":[45],"patch":[46,123],"represents":[47],"small":[49],"image":[50,118],"region,":[51],"and":[52,58,72,83,102,108,122,128,146],"uses":[53],"cosine":[54],"similarity":[55],"detect":[57],"localize":[59],"anomalies":[60],"without":[61],"prior":[62],"training.":[63,149],"Two":[64],"strategies":[65],"are":[66],"compared:":[67],"Method":[68,73,87,90],"I":[69],"(all":[70],"patches)":[71],"II":[74,88],"(least":[75],"similar":[76],"patches).":[77],"Experiments":[78],"on":[79],"MVTec":[80],"AD,":[81],"VisA,":[82],"KSDD2":[84],"show":[85],"that":[86],"outperforms":[89],"I,":[91],"Area":[93],"Under":[94],"the":[95,114,140],"Curve":[96],"improvements":[97],"6":[99],"\u2212":[100],"8%":[101],"achieved":[103],"results":[104],"91.3%,":[106],"82.8%,":[107],"92.8%,":[109],"respectively.":[110],"study":[112],"underscores":[113],"significance":[115],"reference":[117],"diversity,":[119],"object":[120],"orientation,":[121],"selection.":[124],"approach\u2019s":[126],"simplicity":[127],"adaptability":[129],"make":[130],"it":[131],"scalable":[133],"solution":[134],"for":[135,142],"visual":[137],"inspection,":[138],"eliminating":[139],"need":[141],"extensive":[143],"labeled":[144],"data":[145],"individualized":[147]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-11T00:00:00"}