Papers
2
Total Citations
11
H-Index
2
About
Huu Tho Tran is a researcher specializing in computer vision applications for critical infrastructure, with a particular focus on power grid automation and inspection robotics. His work addresses the dangerous, time-consuming nature of manual power line inspections by developing intelligent vision systems that enable autonomous monitoring. Tran’s most cited paper, "A Computer Vision System for Power Transmission Line Inspection Robot" (2021, 6 citations), proposes a framework for robotic inspection of power grids to prevent outages and mitigate risks. His second highly cited work, "Computer Vision System for Reading Analog Gauges at Power Substation" (2021, 5 citations), presents dual algorithms for interpreting oil level, winding temperature, and SF6 gas density gauges—each requiring distinct approaches due to their differing visual characteristics. Together, these contributions demonstrate Tran’s impact in bridging computer vision and energy infrastructure, offering practical solutions for automating hazardous inspection tasks. His research is particularly relevant for students and engineers interested in robotics, industrial automation, and the application of deep learning to real-world safety-critical systems.
Research Focus
Key Achievements
Top Papers
- 1A Computer Vision System for Power Transmission Line Inspection Robot6 citations · 2021
- 2Computer Vision System for Reading Analog Gauges at Power Substation5 citations · 2021