International Journal of Academic Engineering Research (IJAER)   Year: 2019 | Volume: 3 | Issue: 12 | Page No.: 22-29 Mango Classification Using Deep Learning Alaa Soliman Abu Mettleq, Ibtesam M. Dheir, Abeer A. Elsharif, Samy S. Abu-Naser Abstract: In worldwide, there are several hundred cultivars of mango. Depending on the cultivar, mango fruit varies in size, shape, sweetness, skin color, and flesh color which may be pale yellow, gold, or orange. Where there are more than 15 types of manga. In this paper, two types Mango classification approach is presented with a dataset that contains approximately 1200 images. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used, for this task. The results found that CNN-driven Mango classification applications when used in classification automation it enables people to know the type of mango properly. The trained model achieved an accuracy of 100% on test set, demonstrating the feasibility of this approach.