Cotton Plant Disease Detection Using Deep Learning

Most of the farmers cultivate cotton in large numbers but one of the biggest issues in recent decades has been the cotton leaf disease which affects crop productivity and money. The diseases named “Leaf Lesions,” “Bacterial Blight,” “Curl virus,” and “Fusarium wilt” have a significant impact on cotton leaves. A front-end application is developed that takes both the uploaded image and the live image from the camera app. Then, convolutional neural network (CNN), a deep learning algorithm, is used in which learnable weights are assigned to an input image and biases are assigned to various objects in the image which differentiates one from the other. The developed application classifies the class of leaf diseases according to the crop features and then provides a cure for the plant illness containing the name, cost, and description of the pesticide. It also displays major driving factors for cotton production and varieties of cotton in India. In this research work, crops are categorized according to the foundation of color, and experimental results prove that it provides a recognition accuracy of 95% and performs better than the current algorithms.