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2020 – today
- 2023
[c13]Jaeyoung Kim, Seo Taek Kong, Dongbin Na, Kyu-Hwan Jung:
Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection. AAAI 2023: 8246-8254- [c12]Gitaek Kwon, Jaeyoung Kim, Hong-Jun Choi, Byung-Moo Yoon, Sungchul Choi, Kyu-Hwan Jung:
Improving Out-of-Distribution Detection Performance using Synthetic Outlier Exposure Generated by Visual Foundation Models. BMVC 2023: 10-11 - [i7]Jaeyoung Kim, Seo Taek Kong, Dongbin Na, Kyu-Hwan Jung:
Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection. CoRR abs/2301.13012 (2023) - 2022
- [j9]Minki Chung, Seo Taek Kong, Beomhee Park, Younjoon Chung, Kyu-Hwan Jung
, Joon Beom Seo:
Utilizing Synthetic Nodules for Improving Nodule Detection in Chest Radiographs. J. Digit. Imaging 35(4): 1061-1068 (2022) - [c11]Wooseok Jung, Chong Hyun Suh, Woo-Hyun Shim, Jinyoung Kim, Dongsoo Lee, Changhyun Park, Seo Taek Kong, Kyu-Hwan Jung, Hwon Heo, Sang Joon Kim:
Volume is All You Need: Improving Multi-task Multiple Instance Learning for WMH Segmentation and Severity Estimation. MLCN@MICCAI 2022: 23-31 - [c10]Hyeongsub Kim, Seo Taek Kong, Hongseok Lee, Kyungdoc Kim, Kyu-Hwan Jung:
Abstraction in Pixel-wise Noisy Annotations Can Guide Attention to Improve Prostate Cancer Grade Assessment. MILLanD@MICCAI 2022: 23-31 - [c9]Dongsoo Lee, Chong Hyun Suh, Jinyoung Kim, Wooseok Jung, Changhyun Park, Kyu-Hwan Jung, Seo Taek Kong, Woo-Hyun Shim, Hwon Heo, Sang Joon Kim:
Augmenting Magnetic Resonance Imaging with Tabular Features for Enhanced and Interpretable Medial Temporal Lobe Atrophy Prediction. MLCN@MICCAI 2022: 125-134 - [c8]Seo Taek Kong, Soomin Jeon, Dongbin Na, Jaewon Lee, Hong-Seok Lee, Kyu-Hwan Jung:
A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity. NeurIPS 2022 - 2021
- [i6]Seo Taek Kong, Soomin Jeon, Jaewon Lee, Hongseok Lee, Kyu-Hwan Jung:
Relieving the Plateau: Active Semi-Supervised Learning for a Better Landscape. CoRR abs/2104.03525 (2021) - 2020
- [c7]Byeonguk Bae, Jaewon Lee, Seo Taek Kong, Jinkyeong Sung, Kyu-Hwan Jung:
Manifold Ordinal-Mixup for Ordered Classes in TW3-Based Bone Age Assessment. MICCAI (6) 2020: 662-670
2010 – 2019
- 2019
- [j8]Jaemin Son, Sang Jun Park, Kyu-Hwan Jung:
Towards Accurate Segmentation of Retinal Vessels and the Optic Disc in Fundoscopic Images with Generative Adversarial Networks. J. Digit. Imaging 32(3): 499-512 (2019) - [c6]Woong Bae, Seungho Lee, Yeha Lee, Beomhee Park, Minki Chung, Kyu-Hwan Jung:
Resource Optimized Neural Architecture Search for 3D Medical Image Segmentation. MICCAI (2) 2019: 228-236 - [i5]Woong Bae, Seungho Lee, Yeha Lee, Beomhee Park, Minki Chung, Kyu-Hwan Jung:
Resource Optimized Neural Architecture Search for 3D Medical Image Segmentation. CoRR abs/1909.00548 (2019) - 2018
- [j7]Guk Bae Kim, Kyu-Hwan Jung, Yeha Lee, Hyun-Jun Kim, Namkug Kim, Sanghoon Jun, Joon Beom Seo, David A. Lynch:
Comparison of Shallow and Deep Learning Methods on Classifying the Regional Pattern of Diffuse Lung Disease. J. Digit. Imaging 31(4): 415-424 (2018) - [j6]Yeonwoo Jang, Jaemin Son, Kyu Hyung Park, Sang Jun Park, Kyu-Hwan Jung:
Laterality Classification of Fundus Images Using Interpretable Deep Neural Network. J. Digit. Imaging 31(6): 923-928 (2018) - [c5]Jaemin Son, Sangkeun Kim, Sang Jun Park, Kyu-Hwan Jung:
An Efficient and Comprehensive Labeling Tool for Large-Scale Annotation of Fundus Images. CVII-STENT/LABELS@MICCAI 2018: 95-104 - [c4]Jaemin Son, Woong Bae, Sangkeun Kim, Sang Jun Park, Kyu-Hwan Jung:
Classification of Findings with Localized Lesions in Fundoscopic Images Using a Regionally Guided CNN. COMPAY/OMIA@MICCAI 2018: 176-184 - [i4]Sejin Park, Woochan Hwang, Kyu-Hwan Jung, Joon Beom Seo, Namkug Kim:
False Positive Reduction by Actively Mining Negative Samples for Pulmonary Nodule Detection in Chest Radiographs. CoRR abs/1807.10756 (2018) - [i3]Jaemin Son, Woong Bae, Sangkeun Kim, Sang Jun Park, Kyu-Hwan Jung:
Classification of Findings with Localized Lesions in Fundoscopic Images using a Regionally Guided CNN. CoRR abs/1811.00871 (2018) - [i2]Sejin Park, Woochan Hwang, Kyu-Hwan Jung:
Integrating Reinforcement Learning to Self Training for Pulmonary Nodule Segmentation in Chest X-rays. CoRR abs/1811.08840 (2018) - 2017
- [i1]Jaemin Son, Sang Jun Park, Kyu-Hwan Jung:
Retinal Vessel Segmentation in Fundoscopic Images with Generative Adversarial Networks. CoRR abs/1706.09318 (2017) - 2013
- [j5]Kyu-Hwan Jung, Jaewook Lee:
Probabilistic generative ranking method based on multi-support vector domain description. Inf. Sci. 247: 144-153 (2013) - 2012
- [j4]Namhyoung Kim, Kyu-Hwan Jung, Yong Seog Kim, Jaewook Lee:
Uniformly subsampled ensemble (USE) for churn management: Theory and implementation. Expert Syst. Appl. 39(15): 11839-11845 (2012) - [c3]Namhyoung Kim, Jaewook Lee, Kyu-Hwan Jung, Yong Seog Kim:
A New Ensemble Model for Efficient Churn Prediction in Mobile Telecommunication. HICSS 2012: 1023-1029 - 2011
- [j3]Kyu-Hwan Jung, Namhyoung Kim, Jaewook Lee:
Dynamic pattern denoising method using multi-basin system with kernels. Pattern Recognit. 44(8): 1698-1707 (2011) - 2010
- [j2]Kyu-Hwan Jung, Daewon Lee, Jaewook Lee:
Fast support-based clustering method for large-scale problems. Pattern Recognit. 43(5): 1975-1983 (2010)
2000 – 2009
- 2009
- [j1]Daewon Lee, Kyu-Hwan Jung, Jaewook Lee:
Constructing Sparse Kernel Machines Using Attractors. IEEE Trans. Neural Networks 20(4): 721-729 (2009) - 2007
- [c2]Hyun-Chul Kim, Kyu-Hwan Jung, Jaewook Lee:
Approximate Sampling Method for Locally Linear Embedding. IJCNN 2007: 592-595 - 2006
- [c1]Kyu-Hwan Jung, Hyun-Chul Kim, Jaewook Lee:
A Novel Learning Network for Option Pricing with Confidence Interval Information. ISNN (2) 2006: 491-497
Coauthor Index
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