Multilayer Convolutional Neural Network for Plant Diseases Detection

Abstract

Plant diseases are causing a significant loss in the agriculture production. The diseases infect the plant leaves, stem and the fruits which cannot be utilized. The main causes of plant diseases are bacteria, fungi and virus. The identification and diagnosis of the diseases are necessary. Many researchers have delved deeper in this field and find suitable techniques to this end. Moreover, these days, Convolution Neural network has attracted the interest of the researchers as it gives better results for image processing. This paper presents a comparative analysis of the various approaches designed to diagnose the diseases in different plant at the initial stage so that preventive measure can be taken to enhance the productivity. Along with this, the role of CNN in detecting the disease in the plants is also described in this paper.