Yehong Shao
Papers
1
Total Citations
41
H-Index
1
About
Dr. Yehong Shao is a leading researcher in intelligent water conservancy and computer vision, whose work bridges the gap between advanced object detection algorithms and practical environmental monitoring. Her primary research focuses on real-time detection systems for water surface management, particularly addressing the critical need for automated identification of river and lake floating objects to prevent water pollution. Dr. Shao’s most impactful contribution is the development of an improved RefineDet architecture for real-time river surface detection, a novel application that adapts state-of-the-art object detection—commonly used in robot navigation and industrial security—to the underexplored domain of water conservancy. Her seminal 2021 paper on this topic has garnered 41 citations, reflecting its significance in launching a new research direction at the intersection of deep learning and aquatic environmental monitoring. By enabling timely cleanup of floating debris, Dr. Shao’s work directly supports river and lake health management, demonstrating how cutting-edge AI can solve pressing ecological challenges. Her research continues to inspire further innovations in intelligent water monitoring systems.
Research Focus
Key Achievements
Top Papers
- 1