Grapes Leaf Disease Detection using Convolutional Neural Network.

Abstract

Grapes a well-known flavourful, bulb-shaped fruits, also called botanically Vitis vinifera. The pulp appears inside its juicy and sweet taste with few pips or seeds. Despite being the world's most generated fruit, grapes productivity has become less due to Its leaf disease. Because of viruses, bacteria, and fungi, it mainly occurs and reduces the proper growth of fruit. The disease primarily attacks the leaf and damages the full grapes plant. So, it is necessary to detect grape leaf disease. A proper diagnosis minimizes the presence of leaf disease. In order to detect grapes leaf disease, we applied the Convolutional Neural Network, a leading deep learning model. It is the major part of our proposed research work. CNN takes part as a good image processing technique. We divided the dataset both for training and testing purposes. The entire research work shows that the proposed model can effectively identify grape leaf disease appropriately. Here, the experimental outcome successfully gives a 98% accuracy rate