Tan Wei Fang
Papers
1
Total Citations
6
H-Index
1
About
Tan Wei Fang is a researcher whose work bridges computer vision and robotics, with a particular focus on intelligent perception systems. Her key research areas include robotic vision, face detection algorithms, and the application of fractal-based analysis to unconventional imaging domains. Her most cited paper, "Face Detection and Auto Positioning for Robotic Vision System" (2015, 6 citations), presents a novel approach that integrates face detection with autonomous positioning, enabling robots to interact more naturally with human environments. This work is notable for its practical implications in human-robot interaction and service robotics. Beyond this, Wei Fang has explored the unique challenges of processing space photogrammetric snapshots captured across multiple spectral ranges, demonstrating how fractal analysis can extract meaningful patterns from data that differs fundamentally from standard color imagery. While her citation count reflects the emerging nature of her contributions, her research stands out for its interdisciplinary ambition—combining computer vision, robotics, and remote sensing. Her work offers valuable insights for students and researchers interested in developing vision systems that operate robustly across diverse and challenging visual environments, from factory floors to orbital platforms.
Research Focus
Key Achievements
Top Papers
- 1Face Detection and Auto Positioning for Robotic Vision System6 citations · 2015