Potato Leaf Disease Recognition Using Deep Learning Model

Abstract

Potatoes are an important part of our global food supply, but they can be affected by a number of diseases. Leaf diseases are particularly damaging to potato yields. Many disorders can be treated successfully if they're diagnosed early and precisely [1]. A survey of machine learning methods for identifying diseases on potato leaves is presented in this study. Our first objective is to provide an overview of the most common illnesses affecting potato leaves and how to recognize them. Next, we discuss how various machine learning techniques, such as decision trees, support vector machines, and convolutional neural networks, have been used to address this problem. In addition, we discuss the limitations and difficulties associated with these methods, including the requirement for large and diverse datasets, the complexity of disease symptoms, and the absence of conventional benchmarks. Additionally, we provide a roadmap for further research in this area.