Classification Of Pistachio Images With The ResNet Deep Learning Model

Avuçlu, Emre

Classification Of Pistachio Images With The ResNet Deep Learning Model

dc.contributor.author	Avuçlu, Emre
dc.date.accessioned	2025-07-30T12:41:57Z
dc.date.available	2025-07-30T12:41:57Z
dc.date.issued	2023
dc.department	Mühendislik Fakültesi
dc.description.abstract	Pistachio, which is grown in many parts of the world today, has an important place in the agricultural economy. In order to maintain this economic value, the post-harvest industrial classification process is very important to obtain efficiency from this harvest. In the process of separating pistachios, an efficient classification process is needed in order for different pistachio species to appeal to different markets. For this reason, the classification process of pistachios is very important. In this study, Kirmizi and Siirt pistachio classification with 2148 images was made using ResNet architecture. After the statistical experimental studies, the highest classification accuracy was obtained from fold-1 as 88.5781% and the Accuracy value was 0.86168 after the classification process.
dc.identifier.doi	10.15316/SJAFS.2023.029
dc.identifier.endpage	300
dc.identifier.issn	2458-8377
dc.identifier.issue	2
dc.identifier.startpage	291
dc.identifier.uri	https://dx.doi.org/10.15316/SJAFS.2023.029
dc.identifier.uri	https://hdl.handle.net/20.500.12451/13665
dc.identifier.volume	37
dc.indekslendigikaynak	TR-Dizin
dc.institutionauthor	Avuçlu, Emre
dc.institutionauthorid	0000-0002-1622-9059
dc.language.iso	en
dc.publisher	Selçuk Üniversitesi Ziraat Fakültesi
dc.relation.ispartof	Selcuk Journal of Agriculture and Food Sciences
dc.relation.publicationcategory	Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Pistachio Classification
dc.subject	Deep Learning
dc.subject	ResNet
dc.title	Classification Of Pistachio Images With The ResNet Deep Learning Model
dc.type	Article