Seung Ho Nam
Papers
1
Total Citations
2
H-Index
1
About
Seung Ho Nam is a researcher specializing in computer vision and privacy-preserving data processing, with a particular focus on intelligent transportation systems and urban surveillance. His work addresses the critical challenge of balancing data utility with individual privacy in real-world applications. Nam’s most notable contribution is the development of a novel license plate de-identification method for indoor parking lot datasets, published in 2024. This technique enables the safe sharing and analysis of surveillance footage by effectively obscuring sensitive information while preserving the visual context needed for traffic flow analysis, vehicle counting, and security monitoring. Although his work is recent, it has already garnered attention, with his key paper receiving 2 citations—a promising start for a researcher tackling an increasingly important issue in the age of smart cities. Nam’s approach stands out for its practicality and adaptability to real-world deployment, making it a valuable resource for researchers and engineers working on privacy-compliant computer vision systems. His ongoing efforts contribute to the broader goal of developing ethical AI technologies that respect personal privacy without compromising functionality.
Research Focus
Key Achievements
Top Papers
- 1