Q. M. Jonathan Wu
University of Windsor, Windsor Dermatology, BC Innovation Council
Papers
9
Total Citations
396
H-Index
7
About
Q. M. Jonathan Wu is a leading researcher in computer vision and robotics, with a focus on underwater image enhancement, semantic segmentation, and robotic manipulation. His work on underwater image co-enhancement, cited 159 times, introduces correlation feature matching and joint learning to correct color distortion and improve visibility in degraded underwater scenes—critical for marine engineering and autonomous underwater vehicles. In semantic segmentation, his fast segmentation framework (126 citations) prioritizes efficiency without sacrificing accuracy, enabling real-time scene perception for autonomous driving and robot navigation. Wu has also advanced industrial robotics through practical 6-D pose estimation with protective correction (50 citations), addressing challenges in complex multi-scene environments. His earlier contributions include vision-based planar grasp planning and crack inspection for concrete bridges using machine vision, demonstrating a broad impact from infrastructure monitoring to assistive robotics. With over 400 citations across his top papers, Wu’s research bridges theoretical innovation and real-world application, making him a key figure in intelligent vision systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Fast Semantic Segmentation for Scene Perception126 citations · 2018
- 3
- 4
- 5Self-supervised monocular depth estimation with direct methods15 citations · 2020
- 6Implementation of vision-based planar grasp planning12 citations · 2000
- 7Vision-based registration for augmented reality-a short survey7 citations · 2015
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- 9