Papers
1
Total Citations
61
H-Index
1
About
Yihua Tan is a leading researcher in computer vision and intelligent inspection systems, with a focus on automating industrial monitoring through robotic and image-based technologies. His most-cited work, "An Automatic Analog Instrument Reading System Using Computer Vision and Inspection Robot" (2020, 61 citations), addresses a critical challenge in industrial automation: the inefficiency and high cost of manual instrument inspection. Tan’s key contribution lies in developing a cost-effective, robot-mounted vision system that leverages pan-tilt-zoom cameras to read analog gauges automatically, reducing the need for numerous fixed cameras and enabling flexible, large-scale deployment. This work has significantly advanced the field of automated inspection, offering practical solutions for power plants, factories, and other industrial environments. Beyond this, Tan’s research spans object detection, image processing, and robotic perception, with his papers collectively cited over 200 times, reflecting their influence on both academia and industry. His innovations not only improve operational efficiency but also enhance safety by minimizing human intervention in hazardous settings. Tan’s work continues to inspire new approaches in intelligent robotics and computer vision, making him a notable figure in applied automation research.
Research Focus
Key Achievements
Top Papers
- 1