Lang Xu
Papers
1
Total Citations
1
H-Index
1
About
Lang Xu is a researcher specializing in computer vision and deep learning applications for infrastructure monitoring, with a particular focus on power systems. His most notable work, "Improved YOLOv5s Method for Nut Detection on Ultra High Voltage Power Towers" (2023), addresses a critical challenge in electrical grid maintenance: the automated detection of small, critical components like nuts on transmission towers. By enhancing the YOLOv5s object detection algorithm, Xu's method improves the accuracy and efficiency of identifying these components, which are vital for structural integrity but often overlooked in standard inspections. This contribution has direct implications for reducing manual inspection risks and enabling drone-based monitoring of high-voltage infrastructure. While his citation count is currently modest at 1, the work represents a practical, applied advance in the intersection of artificial intelligence and power engineering. Xu's research demonstrates how deep learning can be tailored to solve niche, high-stakes problems in industrial settings, offering a template for future studies in automated defect detection and structural health monitoring.
Research Focus
Key Achievements
Top Papers
- 1