4 citations · 7 across the 6 of their papers we have counts for
6 papers
Decoding Neural Correlation of Language-Specific Imagined Speech using EEG Signals
Keon-Woo Lee, Dae-Hyeok Lee, Sung-Jin Kim +1
Speech impairments due to cerebral lesions and degenerative disorders can be devastating. For humans with severe speech deficits, imagined speech in the brain-computer interface ha…
DAL: Feature Learning from Overt Speech to Decode Imagined Speech-based EEG Signals with Convolutional Autoencoder
Dae-Hyeok Lee, Sung-Jin Kim, Seong-Whan Lee
Brain-computer interface (BCI) is one of the tools which enables the communication between humans and devices by reflecting intention and status of humans. With the development of…
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…
Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks
Dae-Hyeok Lee, Dong-Kyun Han, Sung-Jin Kim +2
Brain-computer interface (BCI) is used for communication between humans and devices by recognizing status and intention of humans. Communication between humans and a drone using el…
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…
Towards Brain-Computer Interfaces for Drone Swarm Control
Ji-Hoon Jeong, Dae-Hyeok Lee, Hyung-Ju Ahn +1
Noninvasive brain-computer interface (BCI) decodes brain signals to understand user intention. Recent advances have been developed for the BCI-based drone control system as the dem…