Classification of Grapevine Leaf Types with Vision Transformer Architecture

Viticulture plays an important role in agriculture. Farmers prefer grapevine cultivation because not only its fruit but also its leaves are used in various fields. Both the use and trade of grapevine leaves within the country is an important source of income. Grapevine leaves, which are grown in almost all countries and used as edible, vary in terms of species. Determining and cultivating the species according to their suitability in terms of productivity is important. In this study, artificial intelligence methods were used to classify grapevine leaf species. The dataset consisting of five different classes, including 100 grapevine leaf images for each class, totalling 500 images, was classified using ViT, VGG19 and MobileNet methods. When the methods used in this study to help increase productivity in production are evaluated, ViT method has the best accuracy rate with 94%.