Papers
1
Total Citations
2
H-Index
1
About
De Tang is a researcher at the forefront of intelligent robotics and computer vision, with a particular focus on the automation of traditional musical instruments. His most cited work, "A dulcimer keys positioning method based on improved Roberts operator" (2021, 2 citations), addresses a critical challenge in robotic dulcimer performance: the precise spatial localization of phoneme keys. By enhancing the classic Roberts edge detection operator, Tang developed a visual positioning method that replaces inefficient manual calibration, enabling robots to autonomously map dulcimer key coordinates with greater accuracy and speed. This contribution bridges the gap between traditional craftsmanship and modern automation, advancing the field of robotic musicianship. While his citation count is modest, Tang’s work is notable for its novel application of image processing to a niche yet culturally significant domain—automated folk instrument performance. His research exemplifies how computer vision can be tailored to solve domain-specific problems, offering a foundation for future work in robotic interaction with complex, non-standardized objects. Tang’s approach underscores the potential of interdisciplinary engineering to preserve and innovate upon cultural heritage through technology.
Research Focus
Key Achievements
Top Papers
- 1A dulcimer keys positioning method based on improved Roberts operator2 citations · 2021