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Byung-Woo Hong
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2020 – today
- 2024
- [j28]Sang-Il Han
, Kensuke Nakamura
Splitting of Composite Neural Networks via Proximal Operator With Information Bottleneck. IEEE Access 12: 157-167 (2024) - [j27]Kensuke Nakamura
Generative adversarial networks via a composite annealing of noise and diffusion. Pattern Recognit. 146: 110034 (2024) - [i18]Ziyao Zeng, Daniel Wang, Fengyu Yang, Hyoungseob Park, Yangchao Wu, Stefano Soatto, Byung-Woo Hong, Dong Lao, Alex Wong:
WorDepth: Variational Language Prior for Monocular Depth Estimation. CoRR abs/2404.03635 (2024) - [i17]Ziyao Zeng, Yangchao Wu, Hyoungseob Park, Daniel Wang, Fengyu Yang, Stefano Soatto, Dong Lao, Byung-Woo Hong, Alex Wong:
RSA: Resolving Scale Ambiguities in Monocular Depth Estimators through Language Descriptions. CoRR abs/2410.02924 (2024) - 2023
- [j26]Da Eun Lee
A Continual Learning Algorithm Based on Orthogonal Gradient Descent Beyond Neural Tangent Kernel Regime. IEEE Access 11: 85395-85404 (2023) - [j25]Hyun-Tae Choi
Unsupervised Image to Image Translation With Additional Mask. IEEE Access 11: 110522-110529 (2023) - [i16]Sihan Wang, Fuping Wu, Lei Li, Zheyao Gao, Byung-Woo Hong, Xiahai Zhuang:
Unsupervised Cardiac Segmentation Utilizing Synthesized Images from Anatomical Labels. CoRR abs/2301.06043 (2023) - 2022
- [j24]Kensuke Nakamura
Regularization in Network Optimization via Trimmed Stochastic Gradient Descent With Noisy Label. IEEE Access 10: 34706-34715 (2022) - [j23]Kensuke Nakamura, Stefano Soatto, Byung-Woo Hong:
Stochastic batch size for adaptive regularization in deep network optimization. Pattern Recognit. 129: 108776 (2022) - [c29]Tian Yu Liu
Monitored Distillation for Positive Congruent Depth Completion. ECCV (2) 2022: 35-53 - [c28]Tomislav Dobricki, Yonghee Oh, Haeun Ko, Taeyun Kim, Dongyoung Kim, Byung-Woo Hong:
Comparison of optical flow image preprocessing options for state of the art deep learning models. ICTC 2022: 585-587 - [c27]Tomislav Dobricki, Yoonghee Oh, Haeun Ko, Taeyun Kim, Dongyooung Kim, Byung-Woo Hong:
Incremental Learning for Optical Flow. ICTC 2022: 588-590 - [c26]Tomislav Dobricki, Xiahai Zhuang, Kyoung-Jae Won, Byung-Woo Hong:
Survey on unsupervised learning methods for optical flow estimation. ICTC 2022: 591-594 - [c25]Sihan Wang, Fuping Wu, Lei Li, Zheyao Gao, Byung-Woo Hong, Xiahai Zhuang:
Unsupervised Cardiac Segmentation Utilizing Synthesized Images from Anatomical Labels. STACOM@MICCAI 2022: 349-358 - [i15]Tian Yu Liu, Parth Agrawal, Allison Chen, Byung-Woo Hong, Alex Wong
Monitored Distillation for Positive Congruent Depth Completion. CoRR abs/2203.16034 (2022) - 2021
- [j22]Dahye Kim
Unsupervised Feature Elimination via Generative Adversarial Networks: Application to Hair Removal in Melanoma Classification. IEEE Access 9: 42610-42620 (2021) - [j21]Kensuke Nakamura
Block-cyclic stochastic coordinate descent for deep neural networks. Neural Networks 139: 348-357 (2021) - [j20]Alex Wong
An Adaptive Framework for Learning Unsupervised Depth Completion. IEEE Robotics Autom. Lett. 6(2): 3120-3127 (2021) - [c24]Alex Wong
Small Lesion Segmentation in Brain MRIs with Subpixel Embedding. BrainLes@MICCAI (1) 2021: 75-87 - [c23]Bilel Derbel, Geoffrey Pruvost
Enhancing Moea/d with Escape Mechanisms. CEC 2021: 1163-1170 - [c22]Dahye Kim, Byung-Woo Hong:
Unsupervised Segmentation incorporating Shape Prior via Generative Adversarial Networks. ICCV 2021: 7304-7314 - [c21]Yuna Han, Bilel Derbel, Byung-Woo Hong:
Convolutional Neural Networks based on Random Kernels in the Frequency Domain. ICOIN 2021: 671-673 - [c20]Jaehwan Kim, Bilel Derbel, Byung-Woo Hong:
Motion Estimation via Scale-Space in Unsupervised Deep Learning. ICOIN 2021: 730-731 - [c19]Hyun-Tae Choi
Control the Information of the Image with Anisotropic Diffusion and Isotropic Diffusion for the Image Classification. MMBD/MLIS 2021: 583-589 - [i14]Kensuke Nakamura, Simon Korman, Byung-Woo Hong:
Stabilization of generative adversarial networks via noisy scale-space. CoRR abs/2105.00220 (2021) - [i13]Alex Wong, Xiaohan Fei, Byung-Woo Hong, Stefano Soatto:
An Adaptive Framework for Learning Unsupervised Depth Completion. CoRR abs/2106.03010 (2021) - [i12]Alex Wong, Allison Chen, Yangchao Wu, Safa Cicek, Alexandre Tiard, Byung-Woo Hong, Stefano Soatto:
Small Lesion Segmentation in Brain MRIs with Subpixel Embedding. CoRR abs/2109.08791 (2021) - 2020
- [j19]Hyo-Hun Kim, Byung-Woo Hong:
Segmentation Neural Network Incorporating Scale-Space in the Application of Cardiac MRI. J. Medical Imaging Health Informatics 10(7): 1494-1505 (2020) - [j18]Byung-Woo Hong
Adaptive Regularization of Some Inverse Problems in Image Analysis. IEEE Trans. Image Process. 29: 2507-2521 (2020) - [c18]Hyun-Tae Choi
Anisotropic Diffusion with Deep Learning. MLIS 2020: 40-45 - [i11]Kensuke Nakamura, Stefano Soatto, Byung-Woo Hong:
Stochastic batch size for adaptive regularization in deep network optimization. CoRR abs/2004.06341 (2020) - [i10]Kensuke Nakamura, Byung-Woo Hong:
Regularization in neural network optimization via trimmed stochastic gradient descent with noisy label. CoRR abs/2012.11073 (2020)
2010 – 2019
- 2019
- [j17]Kensuke Nakamura
Adaptive Weight Decay for Deep Neural Networks. IEEE Access 7: 118857-118865 (2019) - [j16]Junghee Cho, Junseok Kwon, Byung-Woo Hong
Adaptive Regularization via Residual Smoothing in Deep Learning Optimization. IEEE Access 7: 122889-122899 (2019) - [i9]Alex Wong, Byung-Woo Hong, Stefano Soatto:
Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction. CoRR abs/1903.07309 (2019) - [i8]Kensuke Nakamura, Byung-Woo Hong:
Adaptive Weight Decay for Deep Neural Networks. CoRR abs/1907.08931 (2019) - [i7]Junghee Cho, Junseok Kwon, Byung-Woo Hong:
Adaptive Regularization via Residual Smoothing in Deep Learning Optimization. CoRR abs/1907.09750 (2019) - 2017
- [j15]Kensuke Nakamura, Byung-Woo Hong:
Hierarchical image segmentation via recursive superpixel with adaptive regularity. J. Electronic Imaging 26(6): 61602 (2017) - [c17]Naeemullah Khan
Coarse-to-Fine Segmentation with Shape-Tailored Continuum Scale Spaces. CVPR 2017: 1733-1742 - [c16]Byung-Woo Hong, Ja-Keoung Koo
Adaptive Regularization in Convex Composite Optimization for Variational Imaging Problems. GCPR 2017: 268-280 - [i6]Byung-Woo Hong, Ja-Keoung Koo, Stefano Soatto:
Multi-Label Segmentation via Residual-Driven Adaptive Regularization. CoRR abs/1702.08336 (2017) - [i5]Byung-Woo Hong, Ja-Keoung Koo, Martin Burger, Stefano Soatto:
Adaptive Regularization of Some Inverse Problems in Image Analysis. CoRR abs/1705.03350 (2017) - [i4]Kensuke Nakamura, Stefano Soatto, Byung-Woo Hong:
Block-Cyclic Stochastic Coordinate Descent for Deep Neural Networks. CoRR abs/1711.07190 (2017) - 2016
- [j14]Kensuke Nakamura, Byung-Woo Hong:
Fast-convergence superpixel algorithm via an approximate optimization. J. Electronic Imaging 25(5): 053035 (2016) - [i3]Ganesh Sundaramoorthi, Naeemullah Khan, Byung-Woo Hong:
Coarse-to-Fine Segmentation With Shape-Tailored Scale Spaces. CoRR abs/1603.07745 (2016) - [i2]Byung-Woo Hong, Ja-Keoung Koo, Hendrik Dirks, Martin Burger:
Adaptive Parameter Balancing for Composite Optimization Problems in Imaging. CoRR abs/1609.02356 (2016) - 2015
- [j13]Ki-Seong Lee
Split-Jaccard Distance of Hierarchical Decompositions for Software Architecture. IEICE Trans. Inf. Syst. 98-D(3): 712-716 (2015) - [j12]Ja-Keoung Koo, Hyo-Hun Kim, Byung-Woo Hong:
Joint estimation of motion and illumination change in a sequence of images. J. Electronic Imaging 24(5): 053027 (2015) - [j11]Byung-Woo Hong
Shape Matching Using Multiscale Integral Invariants. IEEE Trans. Pattern Anal. Mach. Intell. 37(1): 151-160 (2015) - [c15]Rassulzhan Poltayev, Byung-Woo Hong
A Rotational Invariant Non-local Mean. PCM (2) 2015: 371-380 - 2014
- [j10]Omar Arif, Ganesh Sundaramoorthi, Byung-Woo Hong
Tracking Using Motion Estimation With Physically Motivated Inter-Region Constraints. IEEE Trans. Medical Imaging 33(9): 1875-1889 (2014) - [c14]Ganesh Sundaramoorthi, Byung-Woo Hong
FAST LABEL: Easy and Efficient Solution of Joint Multi-label and Estimation Problems. CVPR 2014: 3126-3133 - [i1]Omar Arif, Ganesh Sundaramoorthi, Byung-Woo Hong, Anthony J. Yezzi:
Tracking via Motion Estimation with Physically Motivated Inter-Region Constraints. CoRR abs/1402.1503 (2014) - 2013
- [j9]Jonghye Woo, Piotr J. Slomka, C.-C. Jay Kuo
Multiphase segmentation using an implicit dual shape prior: Application to detection of left ventricle in cardiac MRI. Comput. Vis. Image Underst. 117(9): 1084-1094 (2013) - [j8]Jeong-Heon Kim, Bo-Young Park, Farhan Akram
Multipass Active Contours for an Adaptive Contour Map. Sensors 13(3): 3724-3738 (2013) - [c13]Byung-Woo Hong
A New Model and Simple Algorithms for Multi-label Mumford-Shah Problems. CVPR 2013: 1219-1226 - 2012
- [c12]Ganesh Sundaramoorthi, Byung-Woo Hong, Anthony J. Yezzi:
Motion and deformation estimation from medical imagery by modeling sub-structure interaction and constraints. CompIMAGE 2012: 221-227 - 2011
- [c11]Byung-Woo Hong
Entropy-Scale Profiles for Texture Segmentation. SSVM 2011: 243-254 - 2010
- [j7]Byung-Woo Hong
Segmentation of regions of interest in mammograms in a topographic approach. IEEE Trans. Inf. Technol. Biomed. 14(1): 129-139 (2010)
2000 – 2009
- 2009
- [j6]Byung-Woo Hong
Enforcing local context into shape statistics. Adv. Comput. Math. 31(1-3): 185-213 (2009) - [j5]Kangyu Ni, Byung-Woo Hong
Unsupervised multiphase segmentation: A recursive approach. Comput. Vis. Image Underst. 113(4): 502-510 (2009) - [j4]Jonghye Woo, Byung-Woo Hong
Non-Rigid Ultrasound Image Registration Based on Intensity and Local Phase Information. J. Signal Process. Syst. 54(1-3): 33-43 (2009) - [c10]Jonghye Woo, Piotr J. Slomka
Automated Multi-Modality Registration of 64-Slice Coronary CT Angiography with Myocardial Perfusion Spect. ISBI 2009: 358-361 - [c9]Jonghye Woo, Byung-Woo Hong
Feature-based non-rigid volume registration of serial coronary CT angiography. Image Processing 2009: 72590R - [c8]Jonghye Woo, Byung-Woo Hong
Curve evolution with a dual shape similarity and its application to segmentation of left ventricle. Image Processing 2009: 72593T - 2008
- [j3]Matthew Mellor, Byung-Woo Hong
Locally Rotation, Contrast, and Scale Invariant Descriptors for Texture Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 30(1): 52-61 (2008) - [j2]Sheshadri R. Thiruvenkadam, Tony F. Chan
Segmentation under Occlusions Using Selective Shape Prior. SIAM J. Imaging Sci. 1(1): 115-142 (2008) - [c7]Byung-Woo Hong
The scale of a texture and its application to segmentation. CVPR 2008 - 2007
- [c6]Jonghye Woo, Byung-Woo Hong
Joint Reconstruction and Registration Using Level Sets: Application to the Computer-Aided Ablation of Atrial Fibrillation. FBIT 2007: 504-507 - [c5]Sheshadri R. Thiruvenkadam, Tony F. Chan, Byung-Woo Hong:
Segmentation Under Occlusions Using Selective Shape Prior. SSVM 2007: 191-202 - 2006
- [j1]Siddharth Manay, Daniel Cremers
Integral Invariants for Shape Matching. IEEE Trans. Pattern Anal. Mach. Intell. 28(10): 1602-1618 (2006) - [c4]Byung-Woo Hong
Shape Representation based on Integral Kernels: Application to Image Matching and Segmentation. CVPR (1) 2006: 833-840 - [p1]Siddharth Manay, Daniel Cremers
Integral Invariants and Shape Matching. Statistics and Analysis of Shapes 2006: 137-166 - 2005
- [c3]Byung-Woo Hong
Structural Comparison of Mammograms. BMVC 2005 - 2004
- [c2]Siddharth Manay, Byung-Woo Hong, Anthony J. Yezzi, Stefano Soatto:
Integral Invariant Signatures. ECCV (4) 2004: 87-99 - 2003
- [c1]Byung-Woo Hong, Michael Brady:
A Topographic Representation for Mammogram Segmentation. MICCAI (2) 2003: 730-737
Coauthor Index
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last updated on 2024-11-28 20:32 CET by the dblp team
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