Real-time Power Line Detection Network using Visible Light and Infrared Images. - Hyeyeon Choi; Gyogwon Koo; Bum Jun Kim; Sang Woo Kim (IVCNZ, 2019)

Improved Robustness of Vision Transformer via PreLayerNorm in Patch Embedding. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Dong Gu Lee; Wonseok Jeong; Sang Woo Kim (CoRR, 2021)

Weakly supervised power line detection algorithm using a recursive noisy label update with refined broken line segments. - Hyeyeon Choi; Gyogwon Koo; Bum Jun Kim; Sang Woo Kim (Expert Syst. Appl., 2021)

Guidelines for the Regularization of Gammas in Batch Normalization for Deep Residual Networks. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Dong Gu Lee; Wonseok Jeong; Sang Woo Kim (CoRR, 2022)

Multi-Level Stacked Regression for predicting electricity consumption of Hot Rolling Mill. - Yeon Tak Kim; Bum Jun Kim; Sang Woo Kim (Expert Syst. Appl., 2022)

Attention-Based Multimodal Image Feature Fusion Module for Transmission Line Detection. - Hyeyeon Choi; Jong Pil Yun; Bum Jun Kim; Hyeonah Jang; Sang Woo Kim (IEEE Trans. Ind. Informatics, 2022)

Understanding Gaussian Attention Bias of Vision Transformers Using Effective Receptive Fields. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Sang Woo Kim (BMVC, 2023)

How to use dropout correctly on residual networks with batch normalization. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Donggeon Lee; Sang Woo Kim (UAI, 2023)

Two-Stage Billet Identification Number Recognition Using Label Distribution. - Hyeonah Jang; Hyeyeon Choi; Bum Jun Kim; Sang Woo Kim; Gyogwon Koo (IEEE Access, 2023)

Resolution-Aware Design of Atrous Rates for Semantic Segmentation Networks. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Sang Woo Kim (CoRR, 2023)

Analysis of NaN Divergence in Training Monocular Depth Estimation Model. - Bum Jun Kim; Hyeonah Jang; Sang Woo Kim (CoRR, 2023)

Dead pixel test using effective receptive field. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Dong Gu Lee; Wonseok Jeong; Sang Woo Kim (Pattern Recognit. Lett., 2023)

Smooth momentum: improving lipschitzness in gradient descent. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Sang Woo Kim (Appl. Intell., 2023)

Extending class activation mapping using Gaussian receptive field. - Bum Jun Kim; Gyogwon Koo; Hyeyeon Choi; Sang Woo Kim (Comput. Vis. Image Underst., 2023)

Improved robustness of vision transformers via prelayernorm in patch embedding. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Dong Gu Lee; Wonseok Jeong; Sang Woo Kim (Pattern Recognit., 2023)

The Disappearance of Timestep Embedding in Modern Time-Dependent Neural Networks. - Bum Jun Kim; Yoshinobu Kawahara; Sang Woo Kim (CoRR, 2024)

Stochastic Subsampling With Average Pooling. - Bum Jun Kim; Sang Woo Kim (CoRR, 2024)

Scale Equalization for Multi-Level Feature Fusion. - Bum Jun Kim; Sang Woo Kim (Trans. Mach. Learn. Res., 2024)

On the ideal number of groups for isometric gradient propagation. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Sang Woo Kim (Neurocomputing, 2024)

Steel product number recognition framework using semantic mask-conditioned diffusion model with limited data. - Hyeyeon Choi; Jong Pil Yun; Bum Jun Kim; Hyeonah Jang; WooSang Shin; Sang Woo Kim (J. Ind. Inf. Integr., 2024)

Guidelines for the Regularization of Gammas in Batch Normalization for Deep Residual Networks. - Bum Jun Kim; Hyeyeon Choi; Hyeonah Jang; Sang Woo Kim (ACM Trans. Intell. Syst. Technol., 2024)

Configuring Data Augmentations to Reduce Variance Shift in Positional Embedding of Vision Transformers. - Bum Jun Kim; Sang Woo Kim (AAAI, 2025)

Font conversion for steel product number recognition: A conditioned diffusion model approach. - Taehan Lee; Hyeyeon Choi; Bum Jun Kim; Hyeonah Jang; Donggeon Lee; Sang Woo Kim (Adv. Eng. Informatics, 2025)

Disappearance of Timestep Embedding: A Case Study on Neural ODE and Diffusion Models. - Bum Jun Kim; Yoshinobu Kawahara; Sang Woo Kim (Trans. Mach. Learn. Res., 2025)

Temperature-Free Loss Function for Contrastive Learning. - Bum Jun Kim; Sang Woo Kim (CoRR, 2025)