摘要
阐述一种基于激光点云煤矿巷道去噪方法,包括深度学习点云去噪、统计滤波对煤矿巷道做自动化去噪。探讨综合方式在实际应用中显示出卓越的适应性和鲁棒性,为巷道形变监测任务提供更可靠的点云数据基础。
This paper describes a laser point cloud based denoising method for coal mine tunnels,which includes deep learning point cloud denoising and statistical filtering for automated denoising of coal mine tunnels.It explores the excellent adaptability and robustness of the integrated approach in practical applications,providing a more reliable point cloud data foundation for tunnel deformation monitoring tasks.
作者
高正峰
金大庆
殷向阳
GAO Zhengfeng;JIN Daqing;YIN Xiangyang(Shenyang University of Technology,Liaoning 110159,China)
出处
《电子技术（上海）》
2023年第12期192-193,共2页
Electronic Technology
关键词
激光点云
语义分割去噪
深度学习
laser point cloud
semantic segmentation denoising
deep learning
