Development of an Automated Visibility Analysis Framework for Pavement Markings Based on the Deep Learning Approach
[1] U.S. Department of Transportation Federal Highway Administration. Available onl ine: https:/www.fhwa.dot.gov/policyinformation/statistics/2018/hm15.cfm. [2] GitHub Repository. https:/github.com/microsoft/VoTT (archived in 2018) [3] Redmon, J. Divvala, S. Girshick, R. Farhadi, A. You Only Look Once: Unified, Rea l Time Object Detection. In Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition; IEEE: 2016; Vol. 2016 Decem. https:/doi.or g/10.1109/CVPR.2016.91 [4] Redmon, J. Farhadi, A. YOLO9000: Better, Faster, Stronger. http:/pjreddie.com/yol o9000/ [5]Redmon, J. Farhadi, A. YOLOv3: An Incremental Improvement. http:/arxiv.org/abs /1804.02767 Results
Remote. Sens.