Xiaohang Shi

Bunkyo University

Papers

1

Total Citations

2

H-Index

1

About

Xiaohang Shi is a researcher at the forefront of 3D vision perception for industrial robotics, with a primary focus on developing high-speed, computationally efficient recognition methods. His major contribution lies in addressing a critical gap in the field: while many researchers prioritize accuracy, Shi emphasizes the transformative potential of speed in accelerating industrial production. His most-cited work, "A High-Speed and Computational Cost-Effective 3D Recognition Method With 2D-Edges-Based 4-Points Congruent Set Algorithm" (2024, 2 citations), introduces a novel algorithm that leverages 2D edge information to dramatically reduce computational cost without sacrificing recognition reliability. This approach is particularly significant for real-time applications where rapid object identification is essential. Though early in his citation impact, Shi’s work represents a pragmatic shift toward practical, deployable solutions in manufacturing automation. His research stands out for its clear industrial motivation and innovative use of geometric constraints, marking him as a rising voice in efficient 3D perception.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
A High-Speed and Computational Cost-Effective 3D Recognition Method With 2D-Edges-Based 4-Points Congruent Set Algorithm
2 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Bunkyo University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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