A Deep Learning-Based Hybrid Approach to Detect Fastener Defects in Real-Time

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dc.contributor.authorAydin, Ilhan
dc.contributor.authorSevi, Mehmet
dc.contributor.authorAkin, Erhan
dc.contributor.authorGuclu, Emre
dc.contributor.authorKarakose, Mehmet
dc.contributor.authorAldarwich, Hssen
dc.date.accessioned2024-12-14T22:07:31Z
dc.date.available2024-12-14T22:07:31Z
dc.date.issued2023
dc.departmentMuş Alparslan Üniversitesien_US
dc.description.abstract[Abdtract Not Available]en_US
dc.description.sponsorshipScientific Research Projects Coordination Unit of Firat University [ADEP.22.02]en_US
dc.description.sponsorshipThis work was supported by the Scientific Research Projects Coordination Unit of Firat University. Project number ADEP.22.02.en_US
dc.identifier.doi10.17559/TV-20221020152721
dc.identifier.endpage1468en_US
dc.identifier.issn1330-3651
dc.identifier.issn1848-6339
dc.identifier.issue5en_US
dc.identifier.scopus2-s2.0-85171622944
dc.identifier.scopusqualityQ3
dc.identifier.startpage1461en_US
dc.identifier.urihttps://doi.org/10.17559/TV-20221020152721
dc.identifier.urihttps://hdl.handle.net/20.500.12639/6649
dc.identifier.volume30en_US
dc.identifier.wosWOS:001095802600005
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherUniv Osijek, Tech Facen_US
dc.relation.ispartofTehnicki Vjesnik-Technical Gazetteen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmzKA_20241214
dc.subjectdefect detectionen_US
dc.subjectdeep learningen_US
dc.subjectfasteneren_US
dc.subjectobject detectionen_US
dc.subjectrailway systemen_US
dc.titleA Deep Learning-Based Hybrid Approach to Detect Fastener Defects in Real-Timeen_US
dc.typeArticle

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