International Journal of Academic Information Systems Research (IJAISR)   Year: 2019 | Volume: 3 | Issue: 12 | Page No.: 12-18 Classifying Nuts Types Using Convolutional Neural Network Ibtesam M. Dheir, Alaa Soliman Abu Mettleq, Abeer A. Elsharif, Samy S. Abu-Naser Abstract: Nuts are nutrient-dense foods with complex matrices rich in unsaturated fatty and other bioactive compounds. By virtue of their unique composition, all types of nuts are likely to beneficially impact health outcomes. In this paper, we classified five types of Nuts with a dataset that contains 2868 images. Convolutional Neural Network (CNN) algorithms, a deep learning technique extensively applied to image recognition was used for this task. The trained model achieved an accuracy of 98% on a held-out test set, demonstrating the feasibility of this approach.