Jiying Zhao

University of Ottawa, Keio University

Papers

2

Total Citations

74

H-Index

2

About

Jiying Zhao is a researcher whose work spans intelligent robotics and computer vision, with a particular focus on precision calibration and perceptual image analysis. One of his most significant contributions is a novel method for robot manipulator calibration, which integrates a camera-based measurement system with a neural network algorithm. This approach, detailed in his highly cited 2010 paper (70 citations), dramatically improves positioning accuracy by mapping and correcting errors across the calibration space, offering a practical and efficient solution for industrial automation. Earlier in his career, Zhao explored the intersection of human visual perception and machine processing. His 1997 paper on color image segmentation introduced a fuzzy-logic-based scheme designed to identify and isolate "outstanding objects"—those most visually significant to human observers. By first segmenting an image into rough fuzzy regions and then refining only the perceptually important areas, this work laid groundwork for more intuitive and efficient image analysis. Together, these contributions demonstrate Zhao’s enduring interest in bridging the gap between human-like perception and precise machine control.

Research Focus

Key Achievements

2
H-Index
2
Papers
74
Total Citations
37
Avg Citations/Paper
🏆 Most Cited Paper
Robot manipulator calibration using neural network and a camera-based measurement system
70 citations · 2010
📈 Most Prolific Year: 2010 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of Ottawa, Keio University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago