Research Progress of Crop Disease and Pest Detection Based on Convolutional Neural Network
Crop pests and diseases pose a significant threat to global agricultural production,often lead-ing to substantial economic losses.The application of machine vision and machine learning methods for crop pest and disease monitoring not only enhances detection efficiency,but also facilitates timely preventive meas-ures to reduce losses.Convolutional neural network(CNN),as a prominent deep learning technique,has been widely used in computer vision for image and object recognition,and also has achieved promising a-chieves in crop disease and pest detection.This paper outlined the key aspects and development history of CNN-based techniques for crop disease and pest detection,reviewed the major research directions and ad-vancements in this area,summarized the main issues in current research,and proposed corresponding solu-tions.The aim of this paper was to provide a theoretical basis for CNN application in agriculture and to offer technical supports for the intelligent management of agricultural production.
Crop disease and pest detectionConvolutional neural networkDeep learningComputer vision
万方数据
维普
