RoadAtlas: Intelligent Platform for Automated Road Defect Detection and Asset Management
Abstract
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.
- Publication:
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arXiv e-prints
- Pub Date:
- September 2021
- DOI:
- 10.48550/arXiv.2109.03385
- arXiv:
- arXiv:2109.03385
- Bibcode:
- 2021arXiv210903385C
- Keywords:
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- Computer Science - Computer Vision and Pattern Recognition;
- Computer Science - Artificial Intelligence;
- Computer Science - Machine Learning;
- Computer Science - Multimedia
- E-Print:
- Demonstration slides attached. To view attachments, please download the file listed under "Ancillary files"