Image Based Tomato Leaf Disease Detection
| dc.contributor.author | Kumar, A. | |
| dc.contributor.author | Vani, M. | |
| dc.date.accessioned | 2026-02-06T06:37:24Z | |
| dc.date.issued | 2019 | |
| dc.description.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. | |
| dc.identifier.citation | 2019 10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019, 2019, Vol., , p. - | |
| dc.identifier.uri | https://doi.org/10.1109/ICCCNT45670.2019.8944692 | |
| dc.identifier.uri | https://idr.nitk.ac.in/handle/123456789/31026 | |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | |
| dc.subject | Convolution Neural Network | |
| dc.subject | Deep Learning | |
| dc.subject | Leaf Diseases Detection | |
| dc.title | Image Based Tomato Leaf Disease Detection |