Wenxi Zheng
Papers
1
Total Citations
35
H-Index
1
About
Wenxi Zheng is a leading researcher in underwater computer vision and deep learning, with a focus on overcoming the unique challenges of aquatic environments. Their most influential work introduces an innovative approach to underwater small target detection by integrating YOLOX with MobileViT and double coordinate attention mechanisms. This architecture, detailed in their 2023 paper (35 citations), addresses the severe degradation caused by light absorption, scattering, and color distortion in underwater imaging—problems that conventional detection algorithms fail to solve. By combining lightweight transformer-based feature extraction with attention mechanisms that preserve spatial location information, Zheng’s method achieves robust detection of small, low-contrast targets in turbid waters. This contribution has significant implications for marine robotics, environmental monitoring, and underwater surveillance. Zheng’s work stands out for its practical balance between computational efficiency and detection accuracy, making it suitable for real-time deployment on autonomous underwater vehicles. Their research continues to push the boundaries of what is possible in challenging underwater environments, establishing them as a key innovator in the field of aquatic vision systems.
Research Focus
Key Achievements
Top Papers
- 1