Plant Disease Classification using Alex Net

Abstract —In modern agriculture field, pest and disease identification is a major role of crop cultivation. Image classification by the use of deep convolutional neural networks of training and methodology used the facilitate a quick and easy system implementation. Pests and diseases are a threat to plant production, especially in India, but identification remains to be a challenge in massive scale and automatically. Collecting images from Image Net dataset. The results show that we can effectively detect and recognize the rice diseases and pests including healthy plant class using a deep convolutional neural network, with the best accuracy of 96.50%. The significantly high success rate makes the model a really useful advisory or early warning tool, and an approach that would be further expanded to support an integrated plant disease identification system to work in real cultivation conditions.