Yongfang Wang
Papers
1
Total Citations
2
H-Index
1
About
Yongfang Wang is a researcher whose work lies at the intersection of computer vision and underwater robotics. Her most cited paper, "Comparison of color model for object recognition in underwater robotics competitions" (2014), with 2 citations, provides a foundational analysis of color models—such as RGB, HSV, and YCbCr—for improving object detection in the challenging, low-visibility conditions of underwater environments. This study directly supports the development of more robust autonomous systems for robotics competitions and real-world marine applications. While her citation count is modest, Wang’s contribution is notable for its practical focus on sensor data processing, offering a systematic comparison that aids engineers and researchers in selecting optimal color spaces for underwater vision tasks. Her work underscores the importance of tailored algorithmic approaches in specialized domains, making her a valuable voice in the niche field of underwater robotics. For students and researchers exploring computer vision in aquatic settings, Wang’s paper serves as a concise, applied reference for enhancing recognition accuracy in dynamic, light-scattering environments.
Research Focus
Key Achievements
Top Papers
- 1