深度学习在路面损伤检测中的应用研究
Research on the Application of Deep learning in Pavement Damage Detection
耿慧1
作者信息
- 1. 中国海洋大学工程学院,山东 青岛 266100
- 折叠
摘要
目前,我国已经形成较为完善的公路网络体系,交通状态得到较大改善.随着公路资源的日益充足,越来越多的公路养护问题随之而来.快速、准确地获取道路损伤数据并进行检测是养护工作的重点.自深度学习出现以来,基于深度学习的检测技术在各行业得到广泛应用,也将路面损伤的自动化检测推向新的发展阶段.基于此,综述路面图像数据采集方法以及深度学习技术在路面损伤检测领域的应用.
Abstract
At present,a relatively perfect highway network system has been formed in China,and the traffic state has been greatly improved. Highway resources are increasingly sufficient,followed by more and more highway maintenance problems. Fast and accurate acquisition of road damage data and detection is the focus of maintenance work. Since the emergence of deep learning,the detection technology based on deep learning has been widely used in various industries,and the automatic detection of pavement damage has been pushed to a new stage of development. This paper summarizes the application of road data acquisition methods and deep learning technology in the field of road defect detection.
关键词
深度学习/路面损伤检测/路面损伤图像Key words
deep learning/pavement damage detection/road damage image引用本文复制引用
出版年
2024
NETL
NSTL
万方数据