OVERVIEW OF DIFFERENT MACHINE LEARNING TECHNIQUES FOR PLANT DISEASE DETECTION

Abstract

This paper presents a survey of different machine learning algorithms particularly Deep Learning Algorithms applied in agriculture field. Agriculture is one of the important sources of earning worldwide. With the rapid expansion of human population and food security for all, agriculture sector needs to be boosted so as to increase the yield [1]. Agriculture is facing problems due to shortage of water, soil productivity, natural calamity, plant diseases, pests etc. Plant diseases result in social, economic and environmental losses to farmers [2]. Early detection and precautionary measures can prevent disease from spreading. Timely adapted precautionary measures will aid farmers in maintaining quality of crop and reduce losses, thereby increasing the yield of food crop. Rather than relying on human expects automated reliable deep learning based methods are used by researchers for prediction of plant diseases.