earticle

영어

Sugarcane is an essential crop in the global agriculture industry. There are lot of diseases in plants of growing sugarcane typically involve in five classes. These diseases consist of Mosaic, Red rot, Yellow, Rust and Healthy. Therefore, this study used to train and testi a deep learning model comprising of 2521 Sugar cane image dataset of disease-infected leaves. This research provides a sequential model for the classification of sugar cane using convolutional neural network. This study used sequential network in which ten layers are adjusted for the classification of these Mosaic, Red rot, yellow, Rust and healthy diseases. The accuracy of the proposed method works better in comparison with the previously used techniques.