Quang Nhat Vo
Papers
1
Total Citations
2
H-Index
1
About
Dr. Quang Nhat Vo is a researcher whose work sits at the intersection of computer vision, robotics, and intelligent systems. His early contributions focused on integrating classical computer vision techniques—such as tensor voting and the Hough transform—with machine learning models like Support Vector Machines (SVM) to enable robotic perception and decision-making. This is exemplified in his most-cited work on a chess-playing robot for the Korean game Janggi, where he developed a novel method for detecting and recognizing game pieces in real time, allowing a robot to autonomously assume the role of a human opponent. While his citation count is still growing, this foundational paper demonstrates his ability to combine traditional vision algorithms with modern classification tools to solve practical robotics challenges. Dr. Vo’s research is particularly relevant for students and engineers interested in bridging the gap between low-level image processing and high-level robotic reasoning, offering a tangible example of how integrated systems can bring autonomous gameplay to life.
Research Focus
Key Achievements
Top Papers
- 1Tensor voting, hough transform and SVM integrated in chess playing robot2 citations · 2015