Research on Detection Method of Cement Concrete Pavement Diseases Based on CE-Net Network
The detection of cement concrete pavement diseases is of great significance for road safety and traffic efficiency.To this end,a deep learning based classification algorithm,namely context encoding network,has been introduced.This network can effectively capture advanced feature information of images and retain more spatial information.At the same time,before disease image segmentation,the collected images are subjected to grayscale and smoothing processing.The results show that the proposed context encoding network model has an average accuracy of 99.68%and a recall rate of 98.24%,which is significantly better than other models.This indicates that the proposed network model has significant disease detection performance and can be applied to actual cement concrete pavement disease detection,providing reliable technical support for road surface maintenance projects.
万方数据
维普
