Yishun Li
- Advances in automatic identification of road subsurface distress using ground penetrating radar: State of the art and future trends. In: Automation in Construction, v. 158 (February 2024). (2024):
- Enabling edge computing ability in view-independent vehicle model recognition. In: International Journal of Transportation Science and Technology, v. 14 (June 2024). (2024):
- Understanding traffic bottlenecks of long freeway tunnels based on a novel location-dependent lighting-related car-following model. In: Tunnelling and Underground Space Technology, v. 136 (June 2023). (2023):
- Effective pavement skid resistance measurement using multi‐scale textures and deep fusion network. In: Computer-Aided Civil and Infrastructure Engineering, v. 38, n. 8 (26 April 2023). (2023):
- Deep learning-based pavement subsurface distress detection via ground penetrating radar data. In: Automation in Construction, v. 142 (October 2022). (2022):
- Cross‐scene pavement distress detection by a novel transfer learning framework. In: Computer-Aided Civil and Infrastructure Engineering, v. 36, n. 11 (September 2021). (2021):