A CNN Model for Disease Detection in Potato Leaves

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Pappu Sah Sudi, Nihit Gupta, Kamlesh Kumar Baniya, Ms. Sindhuja Bangari, Dr. Rachana P

Abstract

India is a predominantly agricultural country, and its crop production rate is a key source of concern. We created a strategy to boost agricultural produce rates and prevent disease infection in plants, making farmer work easy to some extent. They can use deep neural Networks, an AI subfield, to detect damaged plants without having to do so manually, and to cure them before it's too late. This study looks at a variety of experiments and suggests that Convolution Neural Networks (CNN) are better at identifying leaf diseases than other methods. CNN also contributes the highest level of disease detection accuracy possible. Keywords: Neural Networks (NN), Convolutional Neural Network (CNN), Architecture, Deep Learning (DL).

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