Detection of the Quality of Zivzik Pomegranate Grown in Siirt Using Deep Learning Methods

dc.contributor.authorYusuf Bilgen
dc.contributor.authorMahmut Kaya
dc.date.accessioned2025-01-10T11:31:35Z
dc.date.available2025-01-10T11:31:35Z
dc.date.issued2025
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description.abstractThis study aims to determine the quality of the Zivzik pomegranate, a fruit unique to the Siirt region whose quality can only be understood by experts engaged in this business with deep learning methods. Since there is no existing database of Zivzik pomegranate, we first visited the Şirvan district of Siirt, where Zivzik pomegranate grows, many times to create a database, and over a thousand pomegranate photographs were taken and labeled. After the Zivzik pomegranate quality dataset was created, the aim was to determine the quality of Zivzik pomegranate using deep learning methods. AlexNet, VGG-16, VGG-19, ResNet, Inception, XCeption, EfficientNet, and MobileNet deep learning models were applied, and the results were evaluated. As a result of the study, the best accuracy value was obtained from the EfficientNetV2 B0 model at 81.83%. In addition to contributing to the scientific literature, our study is expected to contribute positively to the recognition of the Zivzik pomegranate, the regional economy, and the awareness of consumers and producers about agriculture 4.0 applications.
dc.description.sponsorshipIEEE SMCIEEE Turkiye Section
dc.identifier.citationBİLGEN, Y., & Kaya, M. (2024, October). Detection of the Quality of Zivzik Pomegranate Grown in Siirt Using Deep Learning Methods. In 2024 Innovations in Intelligent Systems and Applications Conference (ASYU) (pp. 1-6). IEEE.
dc.identifier.doi10.1109/ASYU62119.2024.10757065
dc.identifier.scopus2-s2.0-85213337766
dc.identifier.urihttps://doi.org/10.1109/ASYU62119.2024.10757065
dc.identifier.urihttps://hdl.handle.net/20.500.12604/8419
dc.indekslendigikaynakScopus
dc.institutionauthorBigen, Yusuf
dc.institutionauthorid0000-0001-6041-6129
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofInnovations in Intelligent Systems and Applications Conference
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Öğrenci
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectdeep learning
dc.subjectnar kalitesinin tespiti
dc.subjecttransfer öğrenme
dc.subjectZivzik narı
dc.titleDetection of the Quality of Zivzik Pomegranate Grown in Siirt Using Deep Learning Methods
dc.typeConference Object

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