Yaxue Wei
Papers
1
Total Citations
41
H-Index
1
About
Yaxue Wei is a researcher focused on the intersection of computer vision and environmental monitoring, with key contributions in real-time object detection for water conservancy applications. Her most cited work, "Real-Time Detection of River Surface Floating Object Based on Improved RefineDet" (2021, 41 citations), addresses a critical gap in applying deep learning to river health management. By enhancing the RefineDet algorithm, Wei developed a system capable of accurately identifying floating debris on water surfaces—a task rarely tackled in the field. This innovation supports timely cleanup of pollutants, directly aiding efforts to prevent water contamination and maintain aquatic ecosystem health. Her research demonstrates how advanced object detection techniques, typically used in robotics and security, can be adapted for environmental sustainability. Wei’s work stands out for its practical impact, offering a scalable solution for real-time monitoring of rivers and lakes. With growing attention to water quality issues, her contributions are increasingly cited by researchers exploring AI-driven environmental surveillance, positioning her as a notable voice in applied computer vision for ecological protection.
Research Focus
Key Achievements
Top Papers
- 1