Identify and Classify CORN Leaf Diseases Using a Deep Neural Network Architecture

Abstract

Disease attacks on vegetable plants must be anticipated and treated promptly to avoid yield loss. The majority of diseases that affect vegetable plants manifest themselves in their leaves or stems. Disease classification using leaf images is now possible due to advancements in deep learning algorithms. The primary objective is to design a system based on deep learning for the prediction and categorization of vegetable leaf disease. Corn vegetable crops are considered in this work. A publicly available dataset was used for training and testing. Convolutional neural network Inception V3 utilized to develop and test the system. As a result, the performance of the system is projected to be at its most significant level.