Recognition of Bean Leaf Diseases Using Neural Network and Machine Learning Techniques

Abstract

Plant leaf diseases have increased in prevalence recently, making it necessary to conduct accurate research. Bean leaf diseases can be prevented from spreading by earlier detection and accurate identification. Diseases of bean leaves have negatively affected bean yield and quality. There are two types of diseases predicted in bean leaves: angular leaf spots and rust. This work includes a contrast between deep learning algorithms and machine learning algorithms-based approaches such as CNN (Convolutional Neural Networks/ConvNet) and its predefined models, K-Nearest Neighbor in short KNN, Support Vector Machine can also have written as SVM, Multinomial Logistic Regression that automate the identification of leaf diseases in bean plant species. As far as known, no one has offered a comparison study for identifying bean leaf disease.