Road Surface Profiling based on Artificial-Neural Networks

Seungho Choi, Seoyeon Kim, Heelim Hong, Y. B. Kim
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Abstract

Recently, monitoring of road surface is a key factor for road maintenance and management. With the advances in the optical methods, the road monitoring systems have been equipped with high accuracy and resolution sensor package. However, most of the existing sensor packages are equipped with expensive equipment such as optical and complex sensors in considering the dynamics of mobile vehicles and dynamic outdoor environments. In this paper, we propose a CNN-based line laser refinement. The proposed system is designed based on the improvement of CNN-based line lasers, and it is more cost-effective than the existing expensive system.
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基于人工神经网络的路面轮廓分析
目前,路面监测已成为道路养护管理的一个关键因素。随着光学方法的发展,道路监测系统已经配备了高精度、高分辨率的传感器包。然而,考虑到移动车辆的动态性和动态的室外环境,现有的大多数传感器封装都配备了昂贵的光学和复杂传感器等设备。本文提出了一种基于cnn的线激光细化方法。该系统是在改进基于cnn的线激光器的基础上设计的,它比现有昂贵的系统更具成本效益。
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