4 citations · 8 across the 14 of their papers we have counts for
5 papers · 1 filter
Classification of Distraction Levels Using Hybrid Deep Neural Networks From EEG Signals
Dae-Hyeok Lee, Sung-Jin Kim, Yeon-Woo Choi
Non-invasive brain-computer interface technology has been developed for detecting human mental states with high performances. Detection of the pilots' mental states is particularly…
Decoding 3D Representation of Visual Imagery EEG using Attention-based Dual-Stream Convolutional Neural Network
Hyung-Ju Ahn, Dae-Hyeok Lee
A deep neural network has been successfully applied to an electroencephalogram (EEG)-based brain-computer interface. However, in most studies, the correlation between EEG channels…
Decoding High-level Imagined Speech using Attention-based Deep Neural Networks
Dae-Hyeok Lee, Sung-Jin Kim, Keon-Woo Lee
Brain-computer interface (BCI) is the technology that enables the communication between humans and devices by reflecting status and intentions of humans. When conducting imagined s…
Towards Natural Brain-Machine Interaction using Endogenous Potentials based on Deep Neural Networks
Hyung-Ju Ahn, Dae-Hyeok Lee, Ji-Hoon Jeong +1
Human-robot collaboration has the potential to maximize the efficiency of the operation of autonomous robots. Brain-machine interface (BMI) would be a desirable technology to colla…
Design of an EEG-based Drone Swarm Control System using Endogenous BCI Paradigms
Dae-Hyeok Lee, Hyung-Ju Ahn, Ji-Hoon Jeong +1
Non-invasive brain-computer interface (BCI) has been developed for understanding users' intentions by using electroencephalogram (EEG) signals. With the recent development of artif…