Sudong Wang
Papers
1
Total Citations
51
H-Index
1
About
Sudong Wang has made significant contributions to the field of intelligent infrastructure monitoring, with a primary focus on automated pavement distress detection using deep learning. Their most cited work, "A pavement distresses identification method optimized for YOLOv5s" (2022, 51 citations), addresses a critical challenge in transportation safety: the timely and accurate identification of road surface defects. By optimizing the YOLOv5s algorithm, Wang developed a method capable of automatically detecting and recognizing various pavement distresses, overcoming limitations such as single object categories and shading effects that had previously hindered real-world application. This work is vital for preventing structural road damage and reducing traffic accidents through proactive maintenance. Wang’s research bridges computer vision and civil engineering, offering practical solutions for smart city infrastructure. With 51 citations and growing recognition, their work is a key reference for researchers developing automated inspection systems. Wang’s contributions underscore the transformative potential of AI in preserving road safety and infrastructure longevity.
Research Focus
Key Achievements
Top Papers
- 1A pavement distresses identification method optimized for YOLOv5s51 citations · 2022