Rice diseases detection using Convolutional Neural Networks: A Survey

Abstract

Crop diseases have become a common part of the agricultural field and with the growth of the agricultural field, these crop diseases are also increasing day by day. Rice crop is one of the main crop and its plantation has spread in almost every region of India and many parts of the globe also. Rice diseases are very common and in recent decades various machine learning techniques have been introduced to detect those diseases. In this paper, we have conducted a survey study on eight major rice diseases namely bacterial leaf blight, false smut, rice hispa, blast, stemborer, sheath blight, brown spot, brown planthopper, and work conducted on them using CNNs technique. The paper is divided into two major parts, first is the survey methodology followed for conducting the work and second is state of the art used for rice disease detection (RDD) using CNNs technique.