Search Results for author: Seung-Hyun Lee

Found 5 papers, 2 papers with code

Cut and Continuous Paste towards Real-time Deep Fall Detection

no code implementations22 Feb 2022 Sunhee Hwang, Minsong Ki, Seung-Hyun Lee, Sanghoon Park, Byoung-Ki Jeon

Deep learning based fall detection is one of the crucial tasks for intelligent video surveillance systems, which aims to detect unintentional falls of humans and alarm dangerous situations.

Image Classification Image Generation +1

Context-aware Dynamics Model for Generalization in Model-Based Reinforcement Learning

2 code implementations ICML 2020 Kimin Lee, Younggyo Seo, Seung-Hyun Lee, Honglak Lee, Jinwoo Shin

Model-based reinforcement learning (RL) enjoys several benefits, such as data-efficiency and planning, by learning a model of the environment's dynamics.

Model-based Reinforcement Learning reinforcement-learning +1

A Study on Stroke Rehabilitation through Task-Oriented Control of a Haptic Device via Near-Infrared Spectroscopy-Based BCI

no code implementations19 Aug 2013 Berdakh Abibullaev, Jinung An, Seung-Hyun Lee, Jeon-Il Moon

This paper presents a study in task-oriented approach to stroke rehabilitation by controlling a haptic device via near-infrared spectroscopy-based brain-computer interface (BCI).

Brain Computer Interface Classification +1

Minimizing inter-subject variability in fNIRS based Brain Computer Interfaces via multiple-kernel support vector learning

no code implementations25 Sep 2012 Berdakh Abibullaev, Jinung An, Seung-Hyun Lee, Sang-Hyeon Jin, Jeon-Il Moon

In this study, we present an algorithm in order to minimize the above-mentioned variabilities and to overcome the time-consuming and usually error-prone calibration time.

Brain Computer Interface

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