PREDICTING THE RICE LEAF DISEASES USING CNN

Abstract

A variety of diseases attack rice, one of India's most widely planted crops, at various phases in the growing process. It is exceedingly difficult for farmers with poor understanding to identify these diseases manually. Automated picture identification systems based on Convolutional Neural Network (CNN) models are showing considerable promise in deep learning research recently. Our deep learning model was created using Transfer Learning on a small dataset because it was difficult to find an image dataset of rice leaf disease. VGG-16 is utilized to train and assess the proposed CNN architecture, which is based on rice field and internet datasets. The proposed model has a 95 percent accuracy rate. Deep Learning, Convolutional Neural Network (CNN), fine-tuning and rice leaf diseases are some of the terms in this index.