Self-supervised Knowledge Distillation Using Singular Value Decomposition. - Seung Hyun Lee 001; Dae Ha Kim; Byung Cheol Song (ECCV (6), 2018)

Graph-based Knowledge Distillation by Multi-head Attention Network. - Seunghyun Lee 001; Byung Cheol Song (BMVC, 2019)

EPrOD: Evolved Probabilistic Object Detector with Diverse Samples. - Jaewoong Choi; Sungwook Lee; Seunghyun Lee 001; Byung Cheol Song (ECCV Workshops (6), 2020)

Channel Pruning Via Gradient Of Mutual Information For Light-Weight Convolutional Neural Networks. - Min Kyu Lee; Seunghyun Lee 001; Sang Hyuk Lee; Byung Cheol Song (ICIP, 2020)

Filter Pruning and Re-Initialization via Latent Space Clustering. - Seunghyun Lee 001; Byeongho Heo; Jung-Woo Ha 001; Byung Cheol Song (IEEE Access, 2020)

Transformation of Non-Euclidean Space to Euclidean Space for Efficient Learning of Singular Vectors. - Seung Hyun Lee 001; Byung Cheol Song (IEEE Access, 2020)

Real-time purchase behavior recognition system based on deep learning-based object detection and tracking for an unmanned product cabinet. - Dae Ha Kim; Seung Hyun Lee 001; Jungho Jeon; Byung Cheol Song (Expert Syst. Appl., 2020)

Interpretable Embedding Procedure Knowledge Transfer via Stacked Principal Component Analysis and Graph Neural Network. - Seunghyun Lee 001; Byung Cheol Song (AAAI, 2021)

Zero-Shot Knowledge Distillation Using Label-Free Adversarial Perturbation With Taylor Approximation. - Kang Il Lee 004; Seunghyun Lee 001; Byung Cheol Song (IEEE Access, 2021)

Vision Transformer for Small-Size Datasets. - Seung Hoon Lee; Seunghyun Lee 001; Byung Cheol Song (CoRR, 2021)

Ensemble Knowledge Guided Sub-network Search and Fine-Tuning for Filter Pruning. - Seunghyun Lee 001; Byung Cheol Song (ECCV (11), 2022)

Image Enhancement for Improved Visibility of Digital Displays Under The Sunlight. - Heejin Lee; Junmin Lee; Seha Jeong; Seunghyun Lee 001; Seungwan Yu; Junho Heo; Byung Cheol Song (ICIP, 2022)

Contextual Gradient Scaling for Few-Shot Learning. - Sang Hyuk Lee; Seunghyun Lee 001; Byung Cheol Song (WACV, 2022)

CFA: Coupled-Hypersphere-Based Feature Adaptation for Target-Oriented Anomaly Localization. - Sungwook Lee; Seunghyun Lee 001; Byung Cheol Song (IEEE Access, 2022)

Improving Vision Transformers to Learn Small-Size Dataset From Scratch. - Seunghoon Lee; Seunghyun Lee 001; Byung Cheol Song (IEEE Access, 2022)

Balanced knowledge distillation for one-stage object detector. - Sungwook Lee; Seunghyun Lee 001; Byung Cheol Song (Neurocomputing, 2022)

Knowledge Transfer via Decomposing Essential Information in Convolutional Neural Networks. - Seunghyun Lee 001; Byung Cheol Song (IEEE Trans. Neural Networks Learn. Syst., 2022)

Stable Quantization-Aware Training with Adaptive Gradient Clipping. - Jihoon Park; Seunghyun Lee 001; Byung Cheol Song (ICEIC, 2023)

Analysis of performance difference when using knowledge distillation of efficient CNN-based super-resolution algorithm. - Min Yoon; Seunghyun Lee 001; Byung Cheol Song (ICEIC, 2023)

Display Visibility Improvement Through Content and Ambient Light-Adaptive Image Enhancement. - Junmin Lee; Heejin Lee; Seunghyun Lee 001; Junho Heo; Jiwon Lee; Byung Cheol Song (IEEE Access, 2023)

TAKDSR: Teacher Assistant Knowledge Distillation Framework for Graphics Image Super-Resolution. - Min Yoon; Seunghyun Lee 001; Byung Cheol Song (IEEE Access, 2023)

Task-Adaptive Pseudo Labeling for Transductive Meta-Learning. - Sanghyuk Lee; Seunghyun Lee 001; Byung Cheol Song (CoRR, 2023)

Data and Model Uncertainty Aware Salient Object Detection. - Heejin Lee; Seunghyun Lee 001; Byung Cheol Song (IEEE Access, 2024)

Real-Time Monte Carlo Denoising With Adaptive Fusion Network. - Junmin Lee; Seunghyun Lee 001; Min Yoon; Byung Cheol Song (IEEE Access, 2024)

Fast Filter Pruning via Coarse-to-Fine Neural Architecture Search and Contrastive Knowledge Transfer. - Seunghyun Lee 001; Byung Cheol Song (IEEE Trans. Neural Networks Learn. Syst., 2024)

Compressing Neural Networks on Limited Computing Resources. - Seunghyun Lee 001; Dongjun Lee; Minju Hyun; Heeje Kim; Byung Cheol Song (IEEE Access, 2025)