Papers
12
Total Citations
227
H-Index
9
About
Hosub Yoon is a leading researcher in human-robot interaction (HRI), specializing in non-cooperative user authentication, speaker and age/gender recognition, and visual perception for service robots. His pioneering work on automated speaker recognition for home service robots, which integrates genetic algorithms and Dempster–Shafer fusion (39 citations), and his non-cooperative user authentication system (45 citations), address the critical challenge of recognizing users who move freely without active participation. Yoon has also advanced age and gender classification from speech using MFCCs and GMMs (33 citations), and developed robust deep-learning methods for age estimation with artificially generated image sets (12 citations). In computer vision, he created real-time hair segmentation with Mobile-Unet (25 citations) and RGB-D-based visual target tracking for person-following robots (9 citations). His recent work evaluates human-care robot services for the elderly (7 citations, 2024), reflecting a growing focus on socially beneficial applications. With over 200 citations across his most cited papers, Yoon’s contributions are foundational to making service robots adaptive, secure, and capable of natural interaction in uncontrolled environments.
Research Focus
Key Achievements
Top Papers
- 1A Non-Cooperative User Authentication System in Robot Environments45 citations · 2007
- 2
- 3Age and Gender Classification for a Home-Robot Service33 citations · 2007
- 4Real-Time Hair Segmentation Using Mobile-Unet25 citations · 2021
- 5
- 6A robust human head detection method for human tracking14 citations · 2006
- 7Visual Processing of Rock, Scissors, Paper Game for Human Robot Interaction14 citations · 2006
- 8Robust Deep Age Estimation Method Using Artificially Generated Image Set12 citations · 2017
- 9
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