Identification of Plant Diseases on Leaves with the Use of Deep Convolutional Neural Networks

Abstract

Early plant disease identification is crucial for disease management in all types of agriculture, but precision farming in particular, in order to achieve the intended output. This procedure has historically been done by hand by visual examination, which takes a lot of time and calls for the help of an experienced farmer or specialist. Automatic disease detection techniques have emerged as a practical option in the agricultural sector because to developments in computer vision and technology. Computer vision algorithms employ the visual changes in the leaves caused by the majority of plant illnesses to diagnose the disease. The use of convolutional neural networks for plant disease diagnosis is suggested in this article. The test accuracy of the suggested Deep CNN model is 97.10%.