Plant Diseases Detection Based on Convolutional Neural Networks (CNN)

Abstract

Because of the rapid population growth and growing interest in food in India, agriculture plays an important role. As a result, it is necessary to boost harvest yield. An infection caused by microorganisms, infection, and organisms is a serious cause of low collect yield. The main objective of this study is to identify plant diseases. Each leaves have a minute diseases like bacterial and fungal disease which can decrease the harvest yield. This can be done by incorporating Convolutional neural network methodology for detecting the plant diseases. This could be processed by capturing digital images for making the technique more reliable. Using the idea of machine learning, PyTorch can be used to separate the plant's leaves from the rest of the plant. While using Convolutional neural network (CNN), detection of the plant disease can be found effectively as it gives the high accuracy of about 96.1 % to cure the infection of the plant disease.