Structural Review on Plants Leaves Disease Classification Using Machine and Deep Learning Methods

Abstract

The agricultural field is considered one of the strongest pillars of any country’s economy. Due to the plant leaves diseases, the quantity and quality of agricultural yield have been affected. The plant leaves disease classification is the most important technique to identify infected areas in plant images. In this review paper, the focus is on cotton and tomato leaves disease classification. Overall world, cotton and tomato are the most common crops widely used in the agricultural fields. There are several research articles for plant leaves disease classification but there is still a need to improve the accuracies of automated disease detection models. Nowadays, real-time plant leaves disease classification is one of the major problems in the agriculture field. In this study, we describe a literature review on different techniques used to classify the plant leaves disease. This paper summarizes and reviews the various machine and deep learning methods. The main concern of this paper is to analyze the limitations of previous research and suggest future directions for researchers.