A2: Adaptive Augmentation for Effectively Mitigating Dataset Bias. - Jaeju An; Taejune Kim; Donggeun Ko; Sangyup Lee; Simon S. Woo (ACCV (7), 2022)

Deepfake Detection for Fake Images with Facemasks. - Sangjun Lee; Donggeun Ko; Jinyong Park; Saebyeol Shin; Donghee Hong; Simon S. Woo (WDC@AsiaCCS, 2022)

Deepfake Detection for Facial Images with Facemasks. - Donggeun Ko; Sangjun Lee; Jinyong Park; Saebyeol Shin; Donghee Hong; Simon S. Woo (CoRR, 2022)

AmpliBias: Mitigating Dataset Bias through Bias Amplification in Few-shot Learning for Generative Models. - Donggeun Ko; Dongjun Lee; Namjun Park; Kyoungrae Noh; Hyeonjin Park; Jaekwang Kim 001 (CIKM, 2023)

MGCMA: Multi-scale Generator with Channel-wise Mask Attention to generate Synthetic Contrast-enhanced Chest Computed Tomography. - Jeongho Kim 007; Yun-Gyoo Lee; Donggeun Ko; Taejune Kim; Soo-Youn Ham; Simon S. Woo (SAC, 2023)

Hierarchical Contrastive Learning with Multiple Augmentation for Sequential Recommendation. - Dongjun Lee; Donggeun Ko; Jaekwang Kim 001 (CoRR, 2023)

LMCG-Net: Integrating LLMs and ECG for LVEF-Based Classification for Pacing Patients. - Wonkyeong Shim; Namjun Park; Donggeun Ko; Hyebin Gwag; Youngjun Park; Seungjung Park; Jaekwang Kim 001 (BIBM, 2024)

DiffInject: Revisiting Debias via Synthetic Data Generation using Diffusion-based Style Injection. - Donggeun Ko; Sangwoo Jo; Dongjun Lee; Namjun Park; Jaekwang Kim 001 (CoRR, 2024)

Debiasing Classifiers by Amplifying Bias with Latent Diffusion and Large Language Models. - Donggeun Ko; Dongjun Lee; Namjun Park; Wonkyeong Shim; Jaekwang Kim 001 (SAC, 2025)

Hierarchical Contrastive Learning with Multiple Augmentations for Sequential Recommendation. - Dongjun Lee; Donggeun Ko; Jaekwang Kim 001 (SAC, 2025)

PacECG-Net: A Multi-modal Approach Integrating LLMs and ECG for LVSD Classification in Pacemaker Patients. - Wonkyeong Shim; Namjun Park; Donggeun Ko; San Kim; Hyebin Gwag; Youngjun Park; Seungjung Park; Jaekwang Kim 001 (SAC, 2025)