Аннотация:Abstract: The use of deep learning models to identify lessions on cotton leaves on the basis of images of the crop in the field is proposed in this article. Its cultivation in tropical regions has made it the target of a wide spectrum of agricultural pests and diseases, and efficient solutions are required. Moreover, the symptoms of the main pests and diseases cannot be differentiated in the initial stages, and the correct identification of a lesion can be difficult for the producer. To help resolve the problem, the present research provides a solution based on deep learning in the screening of cotton leaves which makes it possible to monitor the health of the cotton crop and make better decisions for its management. For this approach, Automatic classifierCNN will be used for classification based on learningwith some training samples of that twocategories. Finally the simulated result shows that used network classifier provides minimum error during training and better accuracy in classification. Keywords: Plant disease, deep learning, CNN, Classification.
