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Leaf Disease Detection using Convolutional Neural Network

The growth of a country is based upon the agricultural as well as its industrial development. In India, the two most commonly used vegetables are tomato and potato. In this article, there is detection of disease in the leaves of the plant so that it is beneficial to both farmers as well as its allied sectors. The importance of leaf disease detection is to ascertain the disease type on the leaves of the plant so that appropriate measures can be taken accordingly. In this, there is the implementation of convolutional neural network to perform this study and get more accurate results. Crop loss can be reduced by diagnosing and controlling plant disease. But early changes are not so much obvious, it fails the farmer to detect it. Too late detection leads our hard work into futile as it cannot be further prevented and cause plant loss which in turn decreases food security. The automated systems provide assistance by speeding up the convergence rate and decreasing the training time. It also promotes the final classification accuracy.