Kumar, A.Vani, M.2026-02-0620192019 10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, 2019, Vol., , p. -https://doi.org/10.1109/ICCCNT45670.2019.8944692https://idr.nitk.ac.in/handle/123456789/31026Leaf diseases are the major problem in agricultural sector, which affects crop production as well as economic profit. Early detection of diseases using deep learning could avoid such a disaster. Currently, Convolutional Neural Network (CNN) is a class of deep learning which is widely used for the image classification task. We have performed experiments with the CNN architecture for detecting disease in tomato leaves. We trained a deep convolutional neural network using PlantVillage dataset of 14,903 images of diseased and healthy plant leaves, to identify the type of leaves. The trained model achieves test accuracy of 99.25%. © 2019 IEEE.Convolution Neural NetworkDeep LearningLeaf Diseases Detection