Deep Learning for Rice Leaf Disease Classification in Smallholder Farms

Abstract

This study proposes a lightweight convolutional neural network for classifying rice leaf diseases from smartphone images captured in Indonesian smallholder farms. Trained on 8,400 field images across four disease classes, the model attains 96.2% accuracy while running on-device, enabling offline diagnosis where connectivity is limited.