Survey on Deep Learning Architectures in Identification of Crop Pests and Diseases

Abstract

India is second in population and 70% of the population depends on agriculture. Agriculture plays an important role and one of the main occupations in India. A constant threat in farmer's life is crop diseases and pests which affects the quality and productivity of crops. Detecting pests in early stages can prevent the severity of crop diseases which is done by image processing. There are many techniques in image processing, one such method is CNN (Convolutional Neural Network) which is effective and accurate is detecting pest and crop diseases. In this paper, we will be reviewing recent papers on different architectures used in detecting crop pests and crop diseases by Convolutional Neural Network. This paper gives a survey of some of the recent works carried out to identify various pests and diseases caused by such pests in different plants/crops that apply neural network techniques to enhance accuracy in identification. This survey helps researchers to evolve further and improve the efficiency.