Classification of Working Memory Performance from EEG with Deep Artificial Neural Networks. - Youngchul Kwak; Woo-Jin Song; Seong-Eun Kim (BCI, 2019)

Recycling: Semi-Supervised Learning With Noisy Labels in Deep Neural Networks. - Kyeongbo Kong; Junggi Lee; Youngchul Kwak; Minsung Kang; Seong Gyun Kim; Woo-Jin Song (IEEE Access, 2019)

Speckle-Noise-Invariant Convolutional Neural Network for SAR Target Recognition. - Youngchul Kwak; Woo-Jin Song; Seong-Eun Kim (IEEE Geosci. Remote. Sens. Lett., 2019)

3D CNN based Multilevel Feature Fusion for Workload Estimation. - Youngchul Kwak; Woo-Jin Song; Byoung-Kyong Min; Seong-Eun Kim (BCI, 2020)

Multilevel Feature Fusion With 3D Convolutional Neural Network for EEG-Based Workload Estimation. - Youngchul Kwak; Kyeongbo Kong; Woo-Jin Song; Byoung-Kyong Min; Seong-Eun Kim (IEEE Access, 2020)

Deep feature normalization using rest state EEG signals for Brain-Computer Interface. - Youngchul Kwak; Woo-Jin Song; Seong-Eun Kim (ICEIC, 2021)

Mitigating Memorization in Sample Selection for Learning with Noisy Labels. - Kyeongbo Kong; Junggi Lee; Youngchul Kwak; Young-Rae Cho; Seong-Eun Kim; Woo-Jin Song (CoRR, 2021)

Penalty based robust learning with noisy labels. - Kyeongbo Kong; Junggi Lee; Youngchul Kwak; Young-Rae Cho; Seong-Eun Kim; Woo-Jin Song (Neurocomputing, 2022)

Subject-Invariant Deep Neural Networks Based on Baseline Correction for EEG Motor Imagery BCI. - Youngchul Kwak; Kyeongbo Kong; Woo-Jin Song; Seong-Eun Kim (IEEE J. Biomed. Health Informatics, 2023)