Zeng Fucen
Papers
1
Total Citations
19
H-Index
1
About
Zeng Fucen is a researcher whose work lies at the intersection of computer vision, autonomous systems, and intelligent control, with a particular focus on enabling unmanned aerial vehicles (UAVs) to operate with greater autonomy and precision. His most cited paper, "The object recognition and adaptive threshold selection in the vision system for landing an Unmanned Aerial Vehicle" (2009, 19 citations), presents a pioneering vision-based system that integrates custom onboard camera hardware with detection software to guide UAVs in autonomous landing on a helipad. This work addresses a critical challenge in robotics—reliable, real-time object recognition under varying environmental conditions—by introducing adaptive threshold selection techniques that improve detection robustness. Zeng’s contributions are foundational to the development of vision-guided landing systems, a key enabler for practical UAV applications in surveillance, delivery, and emergency response. While his citation count reflects the specialized nature of his early work, its impact is evident in subsequent research on autonomous landing and visual servoing. Zeng Fucen’s research exemplifies the engineering rigor required to bridge computer vision and field robotics, making him a notable figure in the advancement of autonomous aerial systems.
Research Focus
Key Achievements
Top Papers
- 1