Detection and Classification of Tomato Crop Disease Using Convolutional Neural Network

Deep learning is a cutting-edge image processing method that still relatively new but produces reliable results. Leaf disease detection and categorization employ variety of deep approaches. Tomatoes are one the most popular vegetables can be found in every kitchen various forms, no matter cuisine. After potato sweet potato, it third widely produced crop. The second-largest tomato grower world India. However, many diseases affect quality quantity crops. This article discusses deep-learning-based strategy for crop detection. A Convolutional-Neural-Network-based technique used classification. Inside model, two convolutional pooling layers used. results experiments show proposed model outperformed pre-trained InceptionV3, ResNet 152, VGG19. CNN achieved 98% training accuracy 88.17% testing accuracy.