Cassava Leaf Disease Detection Using Deep Learning

Abstract

In this study, a clever plan to detect cassava leaves has been developed using a customized fine-tuned deep learning model. Five categories of diseases are used in this study: Cassava Brown Steak Disease (CBSD), Cassava Green Mite (CGM), Cassava Bacterial Blight (CBB), and Cassava Mosaic Disease (CMD) and Health. The results showed an accuracy on the test data obtained was over 77% on original problem using clever data augmentation without affecting the scope of this problem.