Plant Leaf Disease Detection Using Deep Convolution Neural Network Method of Deep Learning

Abstract

                     The plant leaf disease detection research work is based on good healthy agriculture and the economic growth of Indian formers. Agricultural growth is the forming of good vegetables and fruits. Plants and crops in India’s highest production in agricultural lands. The economic growth affected plant diseases.it rectified the loss of farming lands. Produce the healthy crops and vegetables to support in our research plant leaf diseases identified deep neural network method.  The plant leaves are the most common features to reflect the plants and healthy agriculture modules. the basic crops and vegetables are identified as good healthy crops vegetation. the most serious vegetable crop diseases reflected the leaves and crop images. The image processing deep learning approaches using to identified the convolution neural network model (CNN) to find tomato, brinjal, papaya, potato, cucumber, and bottle gourd affected leaves models. The deep learning model trained the system for using Keras to run on the TensorFlow framework. the plant leaves projected to find healthy and diseased leaves. the leaf symptoms of diseased leaves spots of the shot hole, brownish sickness. Unhealthy leaf spots to trained models identified the accuracy of the models achieved 93.99% accuracy. The trained model to develop a good identification model combines with live data and images.