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dc.contributor.authorSeker, Abdulkadir
dc.contributor.authorPeker, Kadir Askin
dc.contributor.authorYuksek, Ahmet Gurkan
dc.contributor.authorDelibas, Emre
dc.date.accessioned2019-07-27T12:10:23Z
dc.date.accessioned2019-07-28T09:46:18Z
dc.date.available2019-07-27T12:10:23Z
dc.date.available2019-07-28T09:46:18Z
dc.date.issued2016
dc.identifier.isbn978-1-5090-1679-2
dc.identifier.urihttps://hdl.handle.net/20.500.12418/7500
dc.description24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEYen_US
dc.descriptionWOS: 000391250900336en_US
dc.description.abstractFabric defect detection have importance in terms of sectoral quality. Automatic systems are developed on the defect detection, in this regard many methods are tried to obtain high precision with image processing studies. In this study, deep learning which distinguishes with multi-layer architectures and reveals high achievement is applied to fabric defect detection. Autoencoder - a deep learning algorithm-that aimed to represent input data via compression or decompression is tried to detect defect of fabrics and it gains acceptable success. The vital goal of this study is to increase achievement of feature extraction by tuning up the autoencoder's input value and hyper parameters.en_US
dc.description.sponsorshipIEEE, Bulent Ecevit Univ, Dept Elect & Elect Engn, Bulent Ecevit Univ, Dept Biomed Engn, Bulent Ecevit Univ, Dept Comp Engnen_US
dc.language.isoturen_US
dc.publisherIEEEen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectdeep learningen_US
dc.subjectfabric defect detectionen_US
dc.subjectautoencoderen_US
dc.subjectfeature extractionen_US
dc.titleFabric Defect Detection using Deep Learningen_US
dc.typeconferenceObjecten_US
dc.relation.journal2016 24TH SIGNAL PROCESSING AND COMMUNICATION APPLICATION CONFERENCE (SIU)en_US
dc.contributor.department[Seker, Abdulkadir -- Yuksek, Ahmet Gurkan -- Delibas, Emre] Cumhuriyet Univ, Bilgisayar Muhendisligi Bolumu, Sivas, Turkey -- [Peker, Kadir Askin] Meliksah Univ, Bilgisayar Muhendisligi Bolumu, Kayseri, Turkeyen_US
dc.identifier.endpage1440en_US
dc.identifier.startpage1437en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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