International Journal of Academic Information Systems Research (IJAISR)   Year: 2022 | Volume: 6 | Issue: 1 | Page No.: 1-8 Six Fruits Classification Using Deep Learning Download PDF Tanseem N. Abu-Jamie, Samy S. Abu-Naser, Mohammed A. Alkahlout, Mohammed A. Aish Abstract: Fruit grading contributes to the improvement of self-pay and packaging systems in large companies and factories such as juice factories, pharmaceutical companies, fruit storage companies and supermarkets. Convolutional neural networks can automatically extract features by directly processing original images, which has attracted wide interest from researchers in fruit classification terms. However, it is difficult to obtain more accurate identification due to the complexity of class similarity.VGG16 has been used to recognize different types of fruit images. Next, the fruit data set which includes 6 classes also created for network model training and evaluation performance. Images of a group of fruits were collected and a deep convolutional neural network was built to identify six types of fruits. Indicating the feasibility of this model, the ratio reached 100%. Inclusive the approach to training real learning models on large, publicly available image data sets offers a clear path toward easy fruit classification. In this paper, a machine learning based approach is presented for classifying and identifying 6 different fruits with a dataset that contains 2677 images.