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20212026
most citedDiversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with Outliers

5 citations · 9 across the 14 of their papers we have counts for

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eess.SP2024

Dataset Refinement for Improving the Generalization Ability of the EEG Decoding Model

Sung-Jin Kim, Dae-Hyeok Lee, Hyeon-Taek Han

Electroencephalography (EEG) is a generally used neuroimaging approach in brain-computer interfaces due to its non-invasive characteristics and convenience, making it an effective…

eess.SP2024

Decoding Fatigue Levels of Pilots Using EEG Signals with Hybrid Deep Neural Networks

Dae-Hyeok Lee, Sung-Jin Kim, Si-Hyun Kim

The detection of pilots' mental states is critical, as abnormal mental states have the potential to cause catastrophic accidents. This study demonstrates the feasibility of using d…

eess.SP2023★ 1 cited

A Distributed Inference System for Detecting Task-wise Single Trial Event-Related Potential in Stream of Satellite Images

Sung-Jin Kim, Heon-Gyu Kwak, Hyeon-Taek Han +3

Brain-computer interface (BCI) has garnered the significant attention for their potential in various applications, with event-related potential (ERP) performing a considerable role…

eess.SP2023

Decoding EEG-based Workload Levels Using Spatio-temporal Features Under Flight Environment

Dae-Hyeok Lee, Sung-Jin Kim, Si-Hyun Kim +1

The detection of pilots' mental states is important due to the potential for their abnormal mental states to result in catastrophic accidents. This study introduces the feasibility…

eess.SP2021★ 3 cited

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…