Papers
1
Total Citations
9
H-Index
1
About
Jingyao Li is a researcher whose work sits at the intersection of computer vision, image processing, and intelligent robotics. Her most cited paper, "Image edge detection based on fusion of wavelet transform and mathematical morphology" (2016, 9 citations), tackles a fundamental challenge in machine vision: improving edge detection accuracy for robotic applications. By fusing wavelet transform with mathematical morphology, Li addresses the problem of missing detection and smoothing artifacts that plague traditional methods, proposing a hybrid approach that enhances the precision of visual perception in automated systems. This contribution is particularly relevant for intelligent cargo handling, where reliable edge detection is critical for robot navigation and object manipulation. While her citation count is modest, Li's work demonstrates a focused effort to bridge theoretical image processing techniques with practical robotics applications. Her research reflects the growing demand for robust, real-time visual systems in industrial automation, and her fusion methodology offers a promising direction for future work in edge detection and machine vision.
Research Focus
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Top Papers
- 1