Xiaohan Sang

Tongji University

Papers

1

Total Citations

86

H-Index

1

About

Xiaohan Sang is a leading researcher in intelligent infrastructure inspection, specializing in the integration of computer vision and robotics for structural health monitoring. Their work focuses on advancing non-destructive evaluation techniques, particularly for reinforced concrete structures. Sang’s most notable contribution is the development of a novel intelligent inspection robot that employs deep stereo vision for three-dimensional concrete damage detection and quantification. This pioneering work, published in 2021 and garnering 86 citations, addresses a critical gap in infrastructure maintenance by moving beyond traditional two-dimensional damage segmentation methods. By enabling accurate 3D crack assessment, Sang’s research enhances the efficiency, safety, and reliability of structural inspections, offering a transformative approach to prolonging the lifespan of aging infrastructure. Their achievements underscore a commitment to merging robotics and artificial intelligence to solve real-world engineering challenges, positioning them as a key innovator in smart infrastructure and automated damage assessment.

Research Focus

Key Achievements

1
H-Index
1
Papers
86
Total Citations
86
Avg Citations/Paper
🏆 Most Cited Paper
A novel intelligent inspection robot with deep stereo vision for three-dimensional concrete damage detection and quantification
86 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Tongji University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago