Plant Disease Detection Using Deep Learning

Abstract

India is an agrarian economy, with three-quarters of its rural population relying on agriculture as their primary means of livelihood. Agriculture shares 17% of the country’s GDP. With rising demands due to the ever-growing population, increasing farm productivity is the need of the hour. However, annually more than one-third of the crop yield is affected by the diseases in India. Thus, identification of the disease in the early stage is essential to provide proper treatment. Traditionally, the disease identification is done by visual examination, which often is done after major damage has already been done to the crop. With the help of state of art technologies like deep learning and cloud computing, the same can be achieved on a real-time basis. With the help of Convolutional Neural Network architectures, researchers propose a system that focuses on detection and identification of the plant disease with a mere click of leaf picture and provides solutions. Furthermore, the system also generates heat maps, which provides insights about disease spread in a region, thereby easing out the data analysis process.