RoadAtlas:道路缺陷自动检测与资产管理智能平台

Zhuoxiao Chen, Yiyun Zhang, Yadan Luo, Zijian Wang, Jinjiang Zhong, Anthony Southon
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引用次数: 2

摘要

随着基于深度学习的智能检测算法的快速发展,道路缺陷自动识别和道路标记解析等方面都取得了很大进展。这可以有效地解决专业检查员手动检查街道的昂贵和耗时的过程。为了实现这一目标,我们提出了RoadAtlas,这是一个新颖的端到端集成系统,可以支持1)道路缺陷检测,2)道路标记解析,3)基于web的仪表板,用于用户呈现和输入数据,以及4)包含结构良好的数据库和开发的api的后端。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RoadAtlas: Intelligent Platform for Automated Road Defect Detection and Asset Management
With the rapid development of intelligent detection algorithms based on deep learning, much progress has been made in automatic road defect recognition and road marking parsing. This can effectively address the issue of an expensive and time-consuming process for professional inspectors to review the street manually. Towards this goal, we present RoadAtlas, a novel end-to-end integrated system that can support 1) road defect detection, 2) road marking parsing, 3) a web-based dashboard for presenting and inputting data by users, and 4) a backend containing a well-structured database and developed APIs.
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