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Title: Image Based Tomato Leaf Disease Detection
Authors: Kumar, A.
Vani, M.
Issue Date: 2019
Citation: 2019 10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, 2019, Vol., , pp.-
Abstract: Leaf 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.
Appears in Collections:2. Conference Papers

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