Detection of Plant Disease Using Machine Learning

Abstract

Detection of diseases in crops is an important aspect to deal with as it affects the productivity of the agricultural yield. The farmer may not realize that the crop is suffering from a disease by looking at the leaves. In this paper, we will be performing Convolutional Neural Networks (CNN) where data needs to be pre-processed and then we need to divide the data into training dataset and test dataset. We will use the tomato leaves dataset to predict whether a tomato plant is healthy or diseased. Finally, we will be giving a user input image and using this model we will be detecting whether the plant is healthy or diseased and which disease it is suffering from which will help in enhancing the life of a farmer by increasing his productivity. Based on this detected information the farmer will be cautious if the plant is diseased and take appropriate actions.