most citedReconstructing ERP Signals Using Generative Adversarial Networks for Mobile Brain-Machine Interface

7 citations · 11 across the 14 of their papers we have counts for

collaborators

16 papers

cs.HC2020

Functional Connectivity of Imagined Speech and Visual Imagery based on Spectral Dynamics

Seo-Hyun Lee, Minji Lee, Seong-Whan Lee

Recent advances in brain-computer interface technology have shown the potential of imagined speech and visual imagery as a robust paradigm for intuitive brain-computer interface co…

cs.LG2020

Automatic Micro-sleep Detection under Car-driving Simulation Environment using Night-sleep EEG

Young-Seok Kweon, Gi-Hwan Shin, Heon-Gyu Kwak +1

A micro-sleep is a short sleep that lasts from 1 to 30 secs. Its detection during driving is crucial to prevent accidents that could claim a lot of people's lives. Electroencephalo…

cs.NE20201 cited

Predicting the Transition from Short-term to Long-term Memory based on Deep Neural Network

Gi-Hwan Shin, Young-Seok Kweon, Minji Lee

Memory is an essential element in people's daily life based on experience. So far, many studies have analyzed electroencephalogram (EEG) signals at encoding to predict later rememb…

eess.SP2020

Decoding Visual Recognition of Objects from EEG Signals based on Attention-Driven Convolutional Neural Network

Jenifer Kalafatovich, Minji Lee, Seong-Whan Lee

The ability to perceive and recognize objects is fundamental for the interaction with the external environment. Studies that investigate them and their relationship with brain acti…

eess.SP2020

Classification of Imagined Speech Using Siamese Neural Network

Dong-Yeon Lee, Minji Lee, Seong-Whan Lee

Imagined speech is spotlighted as a new trend in the brain-machine interface due to its application as an intuitive communication tool. However, previous studies have shown low cla…

eess.SP20207 cited

Reconstructing ERP Signals Using Generative Adversarial Networks for Mobile Brain-Machine Interface

Young-Eun Lee, Minji Lee, Seong-Whan Lee

Practical brain-machine interfaces have been widely studied to accurately detect human intentions using brain signals in the real world. However, the electroencephalography (EEG) s…