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