Zuxiang Situ

Guangdong University of Technology

Papers

1

Total Citations

53

H-Index

1

About

Zuxiang Situ is a prominent researcher in the fields of computer vision, deep learning, and intelligent infrastructure monitoring. His work focuses on developing efficient, real-time detection systems for critical applications, particularly in civil engineering and urban maintenance. Situ’s most notable contribution is the creation of a real-time sewer defect detection framework that integrates the YOLO network with transfer learning and channel pruning algorithms. This innovative approach, detailed in his 2023 paper, has garnered 53 citations, reflecting its significant impact on automated inspection technologies. By enabling rapid, accurate identification of structural flaws in sewer systems, Situ’s research addresses pressing challenges in urban infrastructure management, reducing reliance on manual inspection and improving public safety. His work exemplifies the practical application of AI to real-world problems, blending algorithmic efficiency with engineering needs. Situ’s achievements highlight his role in advancing edge-based computer vision systems, making him a key figure in the intersection of deep learning and smart city development.

Research Focus

Key Achievements

1
H-Index
1
Papers
53
Total Citations
53
Avg Citations/Paper
🏆 Most Cited Paper
Real-time sewer defect detection based on YOLO network, transfer learning, and channel pruning algorithm
53 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Guangdong University of Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago