Identification of durum wheat grains by using hybrid convolution neural network and deep features

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dc.authoridBASARAN, Erdal/0000-0001-8569-2998
dc.authoridCELIK, YUKSEL/0000-0002-7117-9736
dc.authoridDilay, Yusuf/0000-0002-5365-5137
dc.contributor.authorCelik, Yuksel
dc.contributor.authorBasaran, Erdal
dc.contributor.authorDilay, Yusuf
dc.date.accessioned2024-09-29T15:54:33Z
dc.date.available2024-09-29T15:54:33Z
dc.date.issued2022
dc.departmentKarabük Üniversitesien_US
dc.description.abstractConvolution neural network (CNN) is a deep learning technique widely used in object identification and classification. One of the objects that are identified and classified is grain products. We proposed a hybrid CNN model to identify the dataset obtained from 41 different durum wheat grains in the present study. A new deep feature set was created in the proposed model by combining Logits and Pool10 feature layers of the CNN models MobileNetV2 and SqueezeNet. This new feature set has been classified into the support vector machines (SVM) input. As a result of the experimental tests performed with the proposed hybrid model on the durum wheat data set, an accuracy rate of 91.89% was obtained. In addition, within the scope of this study, a unique durum wheat data set was publicly presented to researchers and added to the literature.en_US
dc.identifier.doi10.1007/s11760-021-02094-y
dc.identifier.endpage1142en_US
dc.identifier.issn1863-1703
dc.identifier.issn1863-1711
dc.identifier.issue4en_US
dc.identifier.scopus2-s2.0-85123065623en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage1135en_US
dc.identifier.urihttps://doi.org/10.1007/s11760-021-02094-y
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4135
dc.identifier.volume16en_US
dc.identifier.wosWOS:000742833500001en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer London Ltden_US
dc.relation.ispartofSignal Image and Video Processingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectConvolution neural network (CNN)en_US
dc.subjectMobileNetV2en_US
dc.subjectSqueezeNeten_US
dc.subjectDeep featuresen_US
dc.subjectSupport vector machines (SVM)en_US
dc.titleIdentification of durum wheat grains by using hybrid convolution neural network and deep featuresen_US
dc.typeArticleen_US

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