A Topographic Representation for Mammogram Segmentation. - Byung-Woo Hong; Michael Brady 001 (MICCAI (2), 2003)

Integral Invariant Signatures. - Siddharth Manay; Byung-Woo Hong; Anthony J. Yezzi; Stefano Soatto (ECCV (4), 2004)

Structural Comparison of Mammograms. - Byung-Woo Hong; Michael Brady 001 (BMVC, 2005)

Integral Invariants and Shape Matching. - Siddharth Manay; Daniel Cremers; Byung-Woo Hong; Anthony J. Yezzi; Stefano Soatto (Statistics and Analysis of Shapes, 2006)

Shape Representation based on Integral Kernels: Application to Image Matching and Segmentation. - Byung-Woo Hong; Emmanuel Prados; Stefano Soatto; Luminita A. Vese (CVPR (1), 2006)

Integral Invariants for Shape Matching. - Siddharth Manay; Daniel Cremers; Byung-Woo Hong; Anthony J. Yezzi; Stefano Soatto (IEEE Trans. Pattern Anal. Mach. Intell., 2006)

Joint Reconstruction and Registration Using Level Sets: Application to the Computer-Aided Ablation of Atrial Fibrillation. - Jonghye Woo; Byung-Woo Hong; Sunil Kumar 001; Indranill Basu Ray; C.-C. Jay Kuo (FBIT, 2007)

The scale of a texture and its application to segmentation. - Byung-Woo Hong; Stefano Soatto; Kangyu Ni; Tony F. Chan (CVPR, 2008)

Locally Rotation, Contrast, and Scale Invariant Descriptors for Texture Analysis. - Matthew Mellor; Byung-Woo Hong; Michael Brady 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2008)

Segmentation under Occlusions Using Selective Shape Prior. - Sheshadri R. Thiruvenkadam; Tony F. Chan; Byung-Woo Hong (SIAM J. Imaging Sci., 2008)

Automated Multi-Modality Registration of 64-Slice Coronary CT Angiography with Myocardial Perfusion Spect. - Jonghye Woo; Piotr J. Slomka; Damini Dey; Victor Cheng; Amit Ramesh; Byung-Woo Hong; Daniel S. Berman; C.-C. Jay Kuo; Guido Germano 002 (ISBI, 2009)

Feature-based non-rigid volume registration of serial coronary CT angiography. - Jonghye Woo; Byung-Woo Hong; Damini Dey; Victor Cheng; Amit Ramesh; Ganesh Sundaramoorthi; C.-C. Jay Kuo; Daniel S. Berman; Guido Germano 002; Piotr J. Slomka (Image Processing, 2009)

Curve evolution with a dual shape similarity and its application to segmentation of left ventricle. - Jonghye Woo; Byung-Woo Hong; Amit Ramesh; Guido Germano 002; C.-C. Jay Kuo; Piotr J. Slomka (Image Processing, 2009)

Enforcing local context into shape statistics. - Byung-Woo Hong; Stefano Soatto; Luminita A. Vese (Adv. Comput. Math., 2009)

Unsupervised multiphase segmentation: A recursive approach. - Kangyu Ni; Byung-Woo Hong; Stefano Soatto; Tony F. Chan (Comput. Vis. Image Underst., 2009)

Non-Rigid Ultrasound Image Registration Based on Intensity and Local Phase Information. - Jonghye Woo; Byung-Woo Hong; Chang-Hong Hu; K. Kirk Shung; C.-C. Jay Kuo; Piotr J. Slomka (J. Signal Process. Syst., 2009)

Segmentation of regions of interest in mammograms in a topographic approach. - Byung-Woo Hong; Bong-Soo Sohn (IEEE Trans. Inf. Technol. Biomed., 2010)

Entropy-Scale Profiles for Texture Segmentation. - Byung-Woo Hong; Kangyu Ni; Stefano Soatto (SSVM, 2011)

Motion and deformation estimation from medical imagery by modeling sub-structure interaction and constraints. - Ganesh Sundaramoorthi; Byung-Woo Hong; Anthony J. Yezzi (CompIMAGE, 2012)

A New Model and Simple Algorithms for Multi-label Mumford-Shah Problems. - Byung-Woo Hong; Zhaojin Lu; Ganesh Sundaramoorthi (CVPR, 2013)

Multiphase segmentation using an implicit dual shape prior: Application to detection of left ventricle in cardiac MRI. - Jonghye Woo; Piotr J. Slomka; C.-C. Jay Kuo; Byung-Woo Hong (Comput. Vis. Image Underst., 2013)

Multipass Active Contours for an Adaptive Contour Map. - Jeong-Heon Kim; Bo-Young Park; Farhan Akram; Byung-Woo Hong; Kwang Nam Choi (Sensors, 2013)

FAST LABEL: Easy and Efficient Solution of Joint Multi-label and Estimation Problems. - Ganesh Sundaramoorthi; Byung-Woo Hong (CVPR, 2014)

Tracking via Motion Estimation with Physically Motivated Inter-Region Constraints. - Omar Arif; Ganesh Sundaramoorthi; Byung-Woo Hong; Anthony J. Yezzi (CoRR, 2014)

Tracking Using Motion Estimation With Physically Motivated Inter-Region Constraints. - Omar Arif; Ganesh Sundaramoorthi; Byung-Woo Hong; Anthony J. Yezzi (IEEE Trans. Medical Imaging, 2014)

A Rotational Invariant Non-local Mean. - Rassulzhan Poltayev; Byung-Woo Hong (PCM (2), 2015)

Split-Jaccard Distance of Hierarchical Decompositions for Software Architecture. - Ki-Seong Lee; Byung-Woo Hong; Youngmin Kim; Jaeyeop Ahn; Chan-Gun Lee (IEICE Trans. Inf. Syst., 2015)

Joint estimation of motion and illumination change in a sequence of images. - Ja-Keoung Koo; Hyo-Hun Kim; Byung-Woo Hong (J. Electronic Imaging, 2015)

Shape Matching Using Multiscale Integral Invariants. - Byung-Woo Hong; Stefano Soatto (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Adaptive Parameter Balancing for Composite Optimization Problems in Imaging. - Byung-Woo Hong; Ja-Keoung Koo; Hendrik Dirks; Martin Burger 001 (CoRR, 2016)

Coarse-to-Fine Segmentation With Shape-Tailored Scale Spaces. - Ganesh Sundaramoorthi; Naeemullah Khan; Byung-Woo Hong (CoRR, 2016)

Fast-convergence superpixel algorithm via an approximate optimization. - Kensuke Nakamura 001; Byung-Woo Hong (J. Electronic Imaging, 2016)

Coarse-to-Fine Segmentation with Shape-Tailored Continuum Scale Spaces. - Naeemullah Khan; Byung-Woo Hong; Anthony J. Yezzi; Ganesh Sundaramoorthi (CVPR, 2017)

Adaptive Regularization in Convex Composite Optimization for Variational Imaging Problems. - Byung-Woo Hong; Ja-Keoung Koo; Hendrik Dirks; Martin Burger 001 (GCPR, 2017)

Multi-Label Segmentation via Residual-Driven Adaptive Regularization. - Byung-Woo Hong; Ja-Keoung Koo; Stefano Soatto (CoRR, 2017)

Hierarchical image segmentation via recursive superpixel with adaptive regularity. - Kensuke Nakamura 001; Byung-Woo Hong (J. Electronic Imaging, 2017)

Adaptive Regularization via Residual Smoothing in Deep Learning Optimization. - Junghee Cho; Junseok Kwon; Byung-Woo Hong (IEEE Access, 2019)

Adaptive Weight Decay for Deep Neural Networks. - Kensuke Nakamura 001; Byung-Woo Hong (IEEE Access, 2019)

Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction. - Alex Wong 001; Byung-Woo Hong; Stefano Soatto (CoRR, 2019)

Anisotropic Diffusion with Deep Learning. - Hyun-Tae Choi; Yuna Han; Dahye Kim 003; Seonghoon Ham; Minji Kim 010; Yesol Park; Byung-Woo Hong (MLIS, 2020)

Regularization in neural network optimization via trimmed stochastic gradient descent with noisy label. - Kensuke Nakamura 001; Byung-Woo Hong (CoRR, 2020)

Segmentation Neural Network Incorporating Scale-Space in the Application of Cardiac MRI. - Hyo-Hun Kim; Byung-Woo Hong (J. Medical Imaging Health Informatics, 2020)

Adaptive Regularization of Some Inverse Problems in Image Analysis. - Byung-Woo Hong; Ja-Keoung Koo; Martin Burger 001; Stefano Soatto (IEEE Trans. Image Process., 2020)

Small Lesion Segmentation in Brain MRIs with Subpixel Embedding. - Alex Wong 001; Allison Chen; Yangchao Wu; Safa Cicek; Alexandre Tiard; Byung-Woo Hong; Stefano Soatto (BrainLes@MICCAI (1), 2021)

Enhancing Moea/d with Escape Mechanisms. - Bilel Derbel; Geoffrey Pruvost; Byung-Woo Hong (CEC, 2021)

Unsupervised Segmentation incorporating Shape Prior via Generative Adversarial Networks. - Dahye Kim 003; Byung-Woo Hong (ICCV, 2021)

Convolutional Neural Networks based on Random Kernels in the Frequency Domain. - Yuna Han; Bilel Derbel; Byung-Woo Hong (ICOIN, 2021)

Motion Estimation via Scale-Space in Unsupervised Deep Learning. - Jaehwan Kim; Bilel Derbel; Byung-Woo Hong (ICOIN, 2021)

Control the Information of the Image with Anisotropic Diffusion and Isotropic Diffusion for the Image Classification. - Hyun-Tae Choi; Nahyun Lee; Jewon No; Sangil Han; Jaeho Tak; Hwijin Kim; Haegang Lee; Seonghoon Ham; Byung-Woo Hong (MMBD/MLIS, 2021)

Unsupervised Feature Elimination via Generative Adversarial Networks: Application to Hair Removal in Melanoma Classification. - Dahye Kim 003; Byung-Woo Hong (IEEE Access, 2021)

Stabilization of generative adversarial networks via noisy scale-space. - Kensuke Nakamura 001; Simon Korman; Byung-Woo Hong (CoRR, 2021)

Block-cyclic stochastic coordinate descent for deep neural networks. - Kensuke Nakamura 001; Stefano Soatto; Byung-Woo Hong (Neural Networks, 2021)

An Adaptive Framework for Learning Unsupervised Depth Completion. - Alex Wong 001; Xiaohan Fei; Byung-Woo Hong; Stefano Soatto (IEEE Robotics Autom. Lett., 2021)

Monitored Distillation for Positive Congruent Depth Completion. - Tian Yu Liu; Parth Agrawal; Allison Chen; Byung-Woo Hong; Alex Wong 001 (ECCV (2), 2022)

Comparison of optical flow image preprocessing options for state of the art deep learning models. - Tomislav Dobricki; Yonghee Oh; Haeun Ko; Taeyun Kim; Dongyoung Kim; Byung-Woo Hong (ICTC, 2022)

Incremental Learning for Optical Flow. - Tomislav Dobricki; Yoonghee Oh; Haeun Ko; Taeyun Kim; Dongyooung Kim; Byung-Woo Hong (ICTC, 2022)

Survey on unsupervised learning methods for optical flow estimation. - Tomislav Dobricki; Xiahai Zhuang; Kyoung-Jae Won; Byung-Woo Hong (ICTC, 2022)

Unsupervised Cardiac Segmentation Utilizing Synthesized Images from Anatomical Labels. - Sihan Wang; Fuping Wu; Lei Li 020; Zheyao Gao; Byung-Woo Hong; Xiahai Zhuang (STACOM@MICCAI, 2022)

Regularization in Network Optimization via Trimmed Stochastic Gradient Descent With Noisy Label. - Kensuke Nakamura 001; Bong-Soo Sohn; Kyoung-Jae Won; Byung-Woo Hong (IEEE Access, 2022)

Stochastic batch size for adaptive regularization in deep network optimization. - Kensuke Nakamura 001; Stefano Soatto; Byung-Woo Hong (Pattern Recognit., 2022)

Unsupervised Image to Image Translation With Additional Mask. - Hyun-Tae Choi; Bong-Soo Sohn; Byung-Woo Hong (IEEE Access, 2023)

A Continual Learning Algorithm Based on Orthogonal Gradient Descent Beyond Neural Tangent Kernel Regime. - Da Eun Lee; Kensuke Nakamura 001; Jaeho Tak; Byung-Woo Hong (IEEE Access, 2023)

RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions. - Ziyao Zeng; Yangchao Wu; Hyoungseob Park; Daniel Wang 005; Fengyu Yang; Stefano Soatto; Dong Lao; Byung-Woo Hong; Alex Wong 001 (NeurIPS, 2024)

Splitting of Composite Neural Networks via Proximal Operator With Information Bottleneck. - Sang-Il Han; Kensuke Nakamura 001; Byung-Woo Hong (IEEE Access, 2024)

WorDepth: Variational Language Prior for Monocular Depth Estimation. - Ziyao Zeng; Daniel Wang 005; Fengyu Yang; Hyoungseob Park; Yangchao Wu; Stefano Soatto; Byung-Woo Hong; Dong Lao; Alex Wong 001 (CoRR, 2024)

PriorDiffusion: Leverage Language Prior in Diffusion Models for Monocular Depth Estimation. - Ziyao Zeng; Jingcheng Ni; Daniel Wang 005; Patrick Rim; Younjoon Chung; Fengyu Yang; Byung-Woo Hong; Alex Wong 001 (CoRR, 2024)

Generative adversarial networks via a composite annealing of noise and diffusion. - Kensuke Nakamura 001; Simon Korman; Byung-Woo Hong (Pattern Recognit., 2024)

Inpainting the Degraded Area with Diffusion Model. - Hyun-Tae Choi; Byung-Woo Hong (ICCE, 2025)

Decoupled Latent Diffusion Model for Enhancing Image Generation. - Hyun-Tae Choi; Kensuke Nakamura 001; Byung-Woo Hong (IEEE Access, 2025)

Regularization for Unconditional Image Diffusion Models via Shifted Data Augmentation. - Kensuke Nakamura 001; Bong-Soo Sohn; Simon Korman; Byung-Woo Hong (IEEE Access, 2025)

Progressive Test Time Energy Adaptation for Medical Image Segmentation. - Xiaoran Zhang; Byung-Woo Hong; Hyoungseob Park; Daniel H. Pak; Anne-Marie Rickmann; Lawrence H. Staib; James S. Duncan; Alex Wong 001 (CoRR, 2025)

ETA: Energy-based Test-time Adaptation for Depth Completion. - Younjoon Chung; Hyoungseob Park; Patrick Rim; Xiaoran Zhang; Jihe He; Ziyao Zeng; Safa Cicek; Byung-Woo Hong; James S. Duncan; Alex Wong 001 (CoRR, 2025)