5 papers
Modularity-Free Conflict-Averse Training for Generalized PINNs
Heejo Kong, Beomchul Park, Sung-Jin Kim +1
Physics-informed neural networks (PINNs) have become a powerful framework for solving PDEs by embedding physical laws into differentiable objectives. Despite their advances, traini…
Diversify and Conquer: Open-set Disagreement for Robust Semi-supervised Learning with Outliers
Heejo Kong, Sung-Jin Kim, Gunho Jung +1
Conventional semi-supervised learning (SSL) ideally assumes that labeled and unlabeled data share an identical class distribution, however in practice, this assumption is easily vi…
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…
Neurophysiological Analysis in Motor and Sensory Cortices for Improving Motor Imagination
Si-Hyun Kim, Sung-Jin Kim, Dae-Hyeok Lee
Brain-computer interface (BCI) enables direct communication between the brain and external devices by decoding neural signals, offering potential solutions for individuals with mot…
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…