Sakarya University Journal of Computer and Information Sciences

Yazarlar: Kiyas KAYAALP, Sedat METLEK

Konular:Bilgisayar Bilimleri, Yapay Zeka

DOI:10.35377/saucis.03.02.717452

Anahtar Kelimeler:Apple classification,Deep learning,Image processing,Bruised,Apple

Özet: In the study, it is aimed to classify the apples as rotten and robust by using the deep learning algorithm of the apple images taken from the CAPA database. In the proposed model, the processing steps are image reading, preprocessing and classification of apples, respectively. In the image reading stage, images taken from the image database were used. The applied deep learning architecture consists of introduction, convolutional, activation, pooling, memorization, full connection and conclusion layers. The data used in this architecture are divided into two as 80% training and 20% test data. Four different wavelength, 16 kinds of image combinations were used for the training and testing of the system. At the classification stage, a success rate of 91.25% was achieved in detecting rotten and robust apples. As a result, it is predicted that the proposed model can be used in the fruit processing industry to automatically classify rotten and robust apples.

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