Unsupervised Image Denoising with Frequency Domain Knowledge. - Nahyun Kim; Donggon Jang; Sunhyeok Lee; Bomi Kim; Daeshik Kim (BMVC, 2021)

Strengthening the Transferability of Adversarial Examples Using Advanced Looking Ahead and Self-CutMix. - Donggon Jang; Sanghyeok Son; Dae-Shik Kim (CVPR Workshops, 2022)

Accurate Hippocampus Segmentation Based on Self-supervised Learning with Fewer Labeled Data. - Kassymzhomart Kunanbayev; Donggon Jang; Woojin Jeong; Nahyun Kim; Dae-Shik Kim (MLCN@MICCAI, 2022)

Learning Color Representations for Low-Light Image Enhancement. - Bomi Kim; Sunhyeok Lee; Nahyun Kim; Donggon Jang; Dae-Shik Kim (WACV, 2022)

A Multiple-State Ion Synaptic Transistor Applicable to Abnormal Car Detection with Transfer Learning. - Ji-Man Yu; Gyeongdo Ham; Chungryeol Lee; Jae-Hyeok Lee 001; Joon-Kyu Han; Jin-Ki Kim; Donggon Jang; Nahyun Kim; Moon-Seok Kim; Sung Gap Im; Dae-Shik Kim; Yang-Kyu Choi (Adv. Intell. Syst., 2022)

Temporally Averaged Regression for Semi-Supervised Low-Light Image Enhancement. - Sunhyeok Lee; Donggon Jang; Dae-Shik Kim (CVPR Workshops, 2023)

Maximizing Discrimination Capability of Knowledge Distillation with Energy-based Score. - Seonghak Kim; Gyeongdo Ham; Suin Lee; Donggon Jang; Daeshik Kim (CoRR, 2023)

Maximizing discrimination capability of knowledge distillation with energy function. - Seonghak Kim; Gyeongdo Ham; Suin Lee; Donggon Jang; Daeshik Kim (Knowl. Based Syst., 2024)

Energy-Based Domain Adaptation Without Intermediate Domain Dataset for Foggy Scene Segmentation. - Donggon Jang; Sunhyeok Lee; Gyuwon Choi; Yejin Lee 013; Sanghyeok Son; Dae-Shik Kim (IEEE Trans. Image Process., 2024)

MMR: A Large-scale Benchmark Dataset for Multi-target and Multi-granularity Reasoning Segmentation. - Donggon Jang; Yucheol Cho; Suin Lee; Taehyeon Kim; Daeshik Kim (ICLR, 2025)

Generality-aware self-supervised transformer for multivariate time series anomaly detection. - Yucheol Cho; Jae-Hyeok Lee 001; Gyeongdo Ham; Donggon Jang; Dae-Shik Kim (Appl. Intell., 2025)