A Survey on Plant Disease Detection System
A deep-learning based approach that is based on improved convolution neural networks for the real-time detection of apple leaf diseases can automatically identify the discriminative features of the diseased apple images and detect the types of apple leaf diseases with high accuracy.
Abstract
: Plant diseases are a major threat to plant growth and crop yield and many researchers have expended substantial efforts on detecting plant diseases. Traditionally, visual examination by experts has been carried out to diagnose plant diseases and biological examination is the second option, if necessary. In recent years, through the development of computer technology, machine learning has been widely utilized to train and detect plant diseases and is a satisfactory alternative for the detection of plant diseases. It is easier to realize higher accuracy by using a deep learning approach that is based on convolution neural networks. In this proposed system a deep learning approach that is based on improved convolution neural networks (CNN) for the real-time detection of apple leaf diseases. The proposed deep-learning based approach can automatically identify the discriminative features of the diseased apple images and detect the types of apple leaf diseases with high accuracy.