Recognition of Plant Diseases using Convolutional Neural Network
G. Madhulatha, O. Ramadevi
Abstract
Plant diseases can cause a reduction in the agricultural product quality and production. This is very vital to find out the plant diseases at an early stage for global health and wellbeing. Automatic plant disease detection is becoming a prominent research domain. It provides benefits in monitoring the large crop fields and helps in detecting the symptoms of the disease when they are found on the leaves. In this paper, the primarily focus on finding the plant diseases and which will reduce the crop loss and hence increases the production efficiency. Our proposed work detects the symptoms of plant diseases at the very initial stage and classifies plant disease based on the symptoms using a Deep Learning (DL) technique. The proposed approach recognizes the diseases using a deep CNN, with the best accuracy of 96.50%. This accuracy rate validates the model performance to early advisory or warming tool.