Classification of Pistachio Images Using VGG16 and VGG19 Deep Learning Models

Abstract

The value of the economy provided by pistachios to the countries where they are grown is increasing day by day. From this point of view, the importance of correct classification of pistachios is known. The more accurately the harvested pistachios are classified, the better the monetary return value. In this study, two different classes of pistachios were classified using VGG16 and VGG19 deep learning architectures. There are 2148 pieces of Kirmizi and Siirt Pistachio in the dataset. Experimental studies were carried out with 5-fold crossvalidation. As a result of the experimental studies, the Accuracy value of 0.802117 and the F1-measure value of 0.830593 were obtained from the average of 5 folds from the VGG16 deep learning model. Likewise, the Accuracy value of 0.779404 and the F-measure value as 0.779404 were obtained from the average of 5 folds from the VGG19 deep learning model.