Detection and Classification of Rice Leaf Diseases Using Deep Learning

Abstract

 Leaf disease detection and its classification is compulsory in farming bulk crops by observing symptoms on the leaves. Detecting diseases from the pictures of a plant leaf is becoming the interesting research in the agricultural field, which can be done by using different deep learning techniques. This task is a model framework for recognition and arrangement of rice leaf diseases dependent on the tainted leaves pictures. We have mainly three rice leaf diseases namely Bacterial Leaf Blight, Brown Spot and Leaf Smut. We captured images of leaves in rice crop fields for testing and training datasets. For accurate extraction of features, we used Deep Convolutional Neural Network AlexNet model.