Detection of crop pests and diseases based on deep convolutional neural network and improved algorithm

摘要

Especially in large monoculture-based agricultural settings, an outbreak of pests or diseases can have a major impact on yield or quality of a crop. Advances in image processing based on convolutional neural network (CNN) architecture over the past decade have yielded major improvements in the accuracy of image classification, renewing interest in its application to pest and disease detection.