Detection of leaf disease is very essential in crop growing field these days. Leaf disease detection require huge amount of work, understanding in the plant field. So we can make use of image processing for detection of leaf disease using PYTHON. This paper tells about leaf disease detection using deep CNN. The automatic detection of rice plant diseases are greatly desired in the field of agricultural. In this study, we put forward a novel rice disease detection technique based on Convolutional Neural Networks (CNNs) techniques. Using a dataset of natural images of diseased rice plant leaves captured from agricultural field. CNNs are trained to classify common rice diseases. The proposed CNNs-based model achieves an accuracy of 95%. This accuracy is very high. The results for the detection of rice diseases show the efficiency of the proposed method.


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