MOBILE LASER SCAN DATA FOR ROAD SURFACE DAMAGE DETECTION

11 citations as recorded by crossref.

1. Pothole detection in the woods: a deep learning approach for forest road surface monitoring with dashcams M. Hoseini et al.
2. Artificial intelligence applications in pavement infrastructure damage detection with automated three-dimensional imaging – A systematic review S. Abu Dabous et al.
3. Mobile Laser Scanning Data for the Evaluation of Pavement Surface Distress M. De Blasiis et al.
4. Automated Pothole Condition Assessment in Pavement Using Photogrammetry-Assisted Convolutional Neural Network E. Ranyal et al.
5. Extraction of Vector Data of Region and Line-Type Defects on Road Surface from MMS Point Clouds R. HONMA et al.
6. LiDAR-Driven Innovations in Pavement Distress Detection: A Review Y. Si et al.
7. An extensive bibliometric analysis of pavement deterioration detection using sensors and machine learning: Trends, innovations, and future directions M. Rizelioğlu
8. A data-driven approach for drive-by damage detection in bridges considering the influence of temperature change R. Corbally & A. Malekjafarian
9. Automated pothole condition assessment in pavement using photogrammetry-assisted convolutional neural network E. Ranyal et al.
10. Relative Flatness Analysis in Mobile Pavement Condition Monitoring Using Hybrid Solid-State LiDAR T. Chuang & Y. Chang
11. Bridge roughness scanned by Dual-Wheeled 3D test vehicle and processed by augmented Kalman filter: Theory and application Z. Li et al.