YePeng Wang
Papers
1
Total Citations
2
H-Index
1
About
Dr. YePeng Wang is a leading researcher in underwater computer vision and robotic perception, with a focus on developing deep learning architectures for challenging aquatic environments. His most cited work, the VVNet framework, introduces a novel integration of Vision Transformer and Vision RetNet architectures specifically designed for underwater object detection in robotic picking tasks. This contribution addresses critical challenges in the field, including poor visibility, light attenuation, and color distortion that plague conventional detection methods in underwater settings. With 2 citations to date, this foundational paper has already begun influencing subsequent research in marine robotics and autonomous underwater systems. Dr. Wang's work bridges the gap between state-of-the-art vision transformers and practical deployment on underwater robots, enabling more reliable object recognition for tasks such as seabed sampling, underwater infrastructure inspection, and marine debris collection. His research represents a significant step toward making autonomous underwater vehicles more capable in real-world operations, where robust detection under extreme visual conditions is essential for mission success.
Research Focus
Key Achievements
Top Papers
- 1