Detection of Wheat Crop Quality using Deep Convolution Neural Network

Abstract

To recognition of disease by automatic is the most exciting and difficult issues in computer imaginative and prescient. A novel technique for disease identification is proposed in this paper. The proposed work guides a distinctive taking out solution for distinguishing between hale and hearty and dangerous crop “wheat” plants. To train the neural network “Convolutional Neural Network” (CNN) because of its capability applications, and CNNs have quickly become the go to tool for tackling any image data problem. The identification of disease in crop is one and most exciting or difficult issues in research imaginative and prescient. In this research paper we introduced a novel technique for identifying diseases. The proposed technique proposes the solution for feature extraction for distinguishing between hale and hearty and damaging wheat plants. To teach the model, we use convolutional neural network (CNN) for image categorization.