Seung-Hyuk Jeon
Papers
1
Total Citations
12
H-Index
1
About
Seung-Hyuk Jeon is a researcher whose work lies at the intersection of computer vision and human-robot interaction, with a particular focus on robust age estimation. His most-cited paper, "Robust Deep Age Estimation Method Using Artificially Generated Image Set" (2017, 12 citations), addresses a critical challenge in HRI/HCI: the need for accurate age recognition despite limited training data. Jeon’s key contribution is a novel approach that leverages artificially generated image sets to enhance deep learning models, making them more resilient to real-world variations in lighting, pose, and expression. This work has implications for creating more intuitive and adaptive robotic systems that can tailor their behavior based on a user’s age. By tackling the data scarcity problem in deep learning, Jeon has helped advance the practical deployment of age estimation technologies, laying groundwork for more personalized and socially aware human-machine interactions.
Research Focus
Key Achievements
Top Papers
- 1Robust Deep Age Estimation Method Using Artificially Generated Image Set12 citations · 2017