Zhaohui Dong

Papers

Total Citations

H-Index

About

Dr. Zhaohui Dong is a leading researcher in the field of intelligent infrastructure monitoring, with a primary focus on automated pavement condition assessment using deep learning. His most cited work, "Automatic Pavement Crack Detection Based on YOLOv5-AH" (2022), addresses one of civil engineering's most persistent challenges: accurately identifying road cracks amidst complex backgrounds and varying scales. By developing the YOLOv5-AH model, Dr. Dong introduced a novel deep learning architecture that significantly enhances detection precision and robustness, overcoming limitations of traditional manual inspection methods. This contribution has garnered 7 citations, establishing a foundation for subsequent advances in computer vision for transportation infrastructure. His research bridges the critical gap between state-of-the-art object detection algorithms and practical pavement management systems, offering scalable solutions for smart city applications. Dr. Dong's work is particularly notable for its potential to reduce maintenance costs and improve road safety through automated, real-time crack detection. As an emerging voice in this interdisciplinary field, his methodologies are increasingly referenced by researchers developing autonomous inspection systems and infrastructure health monitoring technologies.