Machine Learning Approaches for Brinjal Leaf Disease Detection

Agriculture is the main source of income for many people in India. But day by day the degradation of the quality of agriculture is exposed by several diseases. The Brinjal Leaves are exposed to various diseases. This study intends to predict the brinjal leaf disease at its early stage. This study reviews the machine-learning approaches used in the disease prediction process. After performing a comparative analysis, a novel methodology is proposed. The proposed approach is developed by considering VGG16, KNN, AdaBoost Classifier, Naïve Bayes, Decision Tree, and SVM models.