A Study on Rice Leaf Disease Using Deep Learning Techniques

Abstract

Rice is the main source of food for many people around the globe.An automatic identification and classification of rice disease are very important in the domain of agriculture.The most common diseases seen in rice crops include bacterial blight, rice blast, brown spot, Tungro, sheath blight, and leaf smut.According to the World Bank, the predicted demand for rice is 57% or less by 2050.Therefore any damage of rice crops is unacceptable.Several diseases affect crop quality and growth. It can be difficult to diagnose a condition using traditional methods. A computerized system, on the other hand, is extremely useful in detecting disease at an early stage, allowing farmers to protect their crops from damage. This research evaluates the literature on several types of diseases in rice crops and makes comparisons based on accuracy, methodologies, and datasets utilizing Deep Learning and Image Processing Techniques.