Mango Leaf disease Classification using deep learning Hybrid Model

Abstract

Plant diseases are essential as they result in a severe reduction in the quality and quantity of agricultural products. Therefore, early detection and diagnosis of these diseases are imperative. To this end, we propose a deep learning-based approach that automates classifying mango leaf diseases. Deep learning-based classification methods like support vector machines classify various image databases and give the best performance in image segmentation. Here we proposed a way to extract deep qualities of Images by customizing the SVM and then applying the SVM and SGD (hybrid) method. We use the Basic Harumanis Mango Leaves 2021 Dataset for this research. Experimental results show that the suggested approach gives an accuracy of 97.7%.