An overview of Deep Learning Models for Foliar Disease Detection in Maize Crop

Abstract

Agriculture is an important sector of Indian economy and India is among the top three global producers of agricultural products. Protecting the crops and producing healthy yields is a prime goal of the agriculture industries. The agricultural crops are susceptible to diseases and demands proactive early diagnosis and treatment. Studies and Research are in progress to find smart methods and techniques for accurate diagnosis of crop diseases to prevent major yield losses and financial losses. The present study outlines the role of Deep Learning in the crop disease detection and discusses the future advancements in maize disease detection. The paper focuses on the Deep Learning techniques used in identification of diseases on maize plant leaf and describes about some common maize diseases and its classification methods. A disease detection process flow is described in the article which explains the steps involved in development of automated disease detection model. The paper shall help readers to gain insight on Deep Learning techniques to solve classification problems and encourage them to proceed for future work in the concerned domain.