Plant Disease Detection and Classification using CNN

Agriculture is one field which has a high impact on life and economic status of human beings. Improper management leads to loss in agricultural products. Diseases are detrimental the plant’s health turn affects its growth. To ensure minimal cultivated crop, it crucial supervise Convolutional Neural Network class Deep learning used majorly for image classification, other mainstream tasks such as segmentation signal processing. The main aim proposed work find solution problem 38 different classes plant diseases detection using simplest approach while making use computing resources achieve better results compared traditional models. VGG16 training model deployed classification diseases. network models employ automatic feature extraction aid input into respective disease classes. This system achieved an average accuracy 94.8% indicating feasibility neural even under unfavorable conditions.