4 citations · 8 across the 14 of their papers we have counts for
5 papers · 1 filter
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…
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…