A Novel Deep Belief Network with Butterfly Optimization Algorithm for the Classification of Paddy Leaf Disease Detection

The widespread presence of a wide variety of diseases during paddy farming is one of the most significant elements that annually contributes to enormous economic losses. These losses occur as a direct result of the widespread prevalence of these diseases. In this paper, a deep learning algorithm using Deep Belief Network (DBN) and a meta-heuristic optimization using Butterfly optimization algorithm (BOA) is used to classify the images to detect the diseases in a Plant Leaf. The steps of classification involve three different process that includes pre-processing, feature extraction and classification. The simulation is conducted in python to test the efficacy of the classifier. The result of simulation shows that the proposed method has obtained higher classification rate than the existing machine learning classifiers. .