Xin Hu

Papers

Total Citations

H-Index

About

Xin Hu is a researcher whose work focuses on computer vision and automation, particularly in the domain of industrial inspection and robotics. Their key contributions lie in developing methods to enhance the accuracy of automated readings from analog instruments—a critical task for substation and industrial monitoring. Hu’s most cited paper, "Tilt correction method of pointer instrument" (2021, 8 citations), addresses a fundamental challenge in robot-based inspection: the reading errors caused by camera tilt relative to the instrument dial. By proposing a correction method based on feature registration, Hu enables more reliable automated meter reading, directly improving the robustness of robotic systems in real-world environments. This work is notable for its practical application in substation automation, where precision is paramount. While early in their career, Hu’s research demonstrates a clear focus on solving tangible engineering problems at the intersection of image processing and robotics. Their contributions are valuable for students and researchers interested in industrial computer vision, sensor calibration, and the deployment of autonomous inspection systems in challenging physical settings.