A Review on Plant Leaf Disease Detection using Deep Learning

Abstract

Identification of plant disease plays an important role as it prevents stunted growth which causes bad effects on yields. As agriculture plays a vital role in the Indian economy and different countries of the world, so there is a need to prevent losses in terms of production, quality, and quantity of agriculture yields due to plant disease. Earlier farmers used to monitor plant disease with the naked eye which was time-consuming and requires a lot of expertise such as being able to identify a disease and disease-causing agent. But nowadays with advancements in technology, smart farming, and automatic techniques, plant disease can be easily identified and proper diagnosis can be done. It reduces a lot of work of monitoring such as in the case of big farms. Also at an early stage, it detects the symptoms of plant disease when they first appear on leaves. This paper reflects the potential of one such method-Plant disease detection using machine learning, using this one can detect plant disease. It includes the use of image processing techniques with the help of a machine learning algorithm to get a clear and defined image or to extract some useful insight from it. The application of machine learning in agriculture discussed in this paper and have shown the experimental results in the form of accuracy and practical useability. Also, Convolution Neural Network (CNN) is used for image classification. CNNs are equipped with input, output, and hidden layers which help in process and in image classification.