Mao Chen
Papers
1
Total Citations
5
H-Index
1
About
Mao Chen is a researcher specializing in computer vision and precision measurement systems, with a particular focus on enhancing the accuracy of distance estimation using monocular visual sensors. Their most cited work, "A new method for increasing accuracy of distance measurement based on single visual camera" (2019), introduces an innovative approach that significantly improves the reliability of spatial data captured by a single camera—a critical advancement for applications in robotics, autonomous navigation, and augmented reality. While the paper has garnered 5 citations, its impact lies in addressing a fundamental challenge in 3D reconstruction and depth perception without the need for expensive multi-camera setups. Chen’s contributions offer a cost-effective solution for real-world environments where precision is paramount, laying groundwork for further developments in visual metrology and sensor fusion. Their work exemplifies the intersection of algorithmic efficiency and practical engineering, making it a valuable reference for researchers exploring low-cost, high-accuracy vision systems.
Research Focus
Key Achievements
Top Papers
- 1