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ORCIDSangheum Hwang
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2020 – today
- 2024
[j18]Carlos Vintimilla
, Sangheum Hwang:
Self-Supervised Representation Learning for Basecalling Nanopore Sequencing Data. IEEE Access 12: 109355-109366 (2024)- [j17]Soojin Lee, Sangheum Hwang:
Context-aware cross feature attentive network for click-through rate predictions. Appl. Intell. 54(19): 9330-9344 (2024) - [j16]Jiin Koo, Sungjoon Choi, Sangheum Hwang:
Generalized Outlier Exposure: Towards a trustworthy out-of-distribution detector without sacrificing accuracy. Neurocomputing 577: 127371 (2024) - [j15]Seungwon Seo, Suho Lee, Sangheum Hwang:
StochCA: A novel approach for exploiting pretrained models with cross-attention. Neural Networks 180: 106663 (2024) - [c7]Jeonghyeon Kim, Jihyo Kim, Sangheum Hwang:
Comparison of Out-of-Distribution Detection Performance of CLIP-based Fine-Tuning Methods. ICEIC 2024: 1-4 - [i15]SeokHyun Seo, Jinwoo Hong, Jungwoo Chae, Kyungyul Kim, Sangheum Hwang:
GTA: Guided Transfer of Spatial Attention from Object-Centric Representations. CoRR abs/2401.02656 (2024) - [i14]Seungwon Seo, Suho Lee, Sangheum Hwang:
StochCA: A Novel Approach for Exploiting Pretrained Models with Cross-Attention. CoRR abs/2402.16092 (2024) - 2023
- [j14]Jihyo Kim, Jiin Koo, Sangheum Hwang:
A unified benchmark for the unknown detection capability of deep neural networks. Expert Syst. Appl. 229(Part A): 120461 (2023) - [j13]Jeongeun Park, Seungyoun Shin, Sangheum Hwang, Sungjoon Choi:
Elucidating robust learning with uncertainty-aware corruption pattern estimation. Pattern Recognit. 138: 109387 (2023) - [i13]Jihyo Kim, Jeonghyeon Kim, Sangheum Hwang:
Deep Active Learning with Contrastive Learning Under Realistic Data Pool Assumptions. CoRR abs/2303.14433 (2023) - [i12]Suho Lee, Seungwon Seo, Jihyo Kim, Yejin Lee, Sangheum Hwang:
Few-shot Fine-tuning is All You Need for Source-free Domain Adaptation. CoRR abs/2304.00792 (2023) - [i11]Jae-Hun Lee, Doyoung Yoon, Byeongmoon Ji, Kyungyul Kim, Sangheum Hwang:
Rethinking Evaluation Protocols of Visual Representations Learned via Self-supervised Learning. CoRR abs/2304.03456 (2023) - 2022
- [j12]Hansub Shin, Sungyong Sim, Hyukyoon Kwon, Sangheum Hwang, Younho Lee:
A new smart smudge attack using CNN. Int. J. Inf. Sec. 21(1): 25-36 (2022) - 2021
- [j11]Jaehoon Koo, Sangheum Hwang:
A Unified Defect Pattern Analysis of Wafer Maps Using Density-Based Clustering. IEEE Access 9: 78873-78882 (2021) - [j10]Sangwoo Lee, Yejin Lee, Geongyu Lee, Sangheum Hwang:
Supervised Contrastive Embedding for Medical Image Segmentation. IEEE Access 9: 138403-138414 (2021) - [j9]Seungyeon Lee, Eunji Jo, Sangheum Hwang, Gyeong Bok Jung, Dohyun Kim:
Similarity based Deep Neural Networks. Int. J. Fuzzy Log. Intell. Syst. 21(3): 205-212 (2021) - [j8]Jaemoon Hwang, Sangheum Hwang:
Exploiting Global Structure Information to Improve Medical Image Segmentation. Sensors 21(9): 3249 (2021) - [c6]Kyungyul Kim, Byeongmoon Ji, Doyoung Yoon, Sangheum Hwang:
Self-Knowledge Distillation with Progressive Refinement of Targets. ICCV 2021: 6547-6556 - [i10]Jeongeun Park, Seungyoun Shin, Sangheum Hwang, Sungjoon Choi:
Elucidating Noisy Data via Uncertainty-Aware Robust Learning. CoRR abs/2111.01632 (2021) - [i9]Jihyo Kim, Jiin Koo, Sangheum Hwang:
A Unified Benchmark for the Unknown Detection Capability of Deep Neural Networks. CoRR abs/2112.00337 (2021) - 2020
- [j7]Sangheum Hwang, Hyeon Gyu Yeo, Jung-Sik Hong:
A New Splitting Criterion for Better Interpretable Trees. IEEE Access 8: 62762-62774 (2020) - [j6]Minyoung Park, Seungyeon Lee, Sangheum Hwang, Dohyun Kim:
Additive Ensemble Neural Networks. IEEE Access 8: 113192-113199 (2020) - [c5]Jooyoung Moon, Jihyo Kim, Younghak Shin, Sangheum Hwang:
Confidence-Aware Learning for Deep Neural Networks. ICML 2020: 7034-7044 - [i8]Kyungyul Kim, Byeongmoon Ji, Doyoung Yoon, Sangheum Hwang:
Self-Knowledge Distillation: A Simple Way for Better Generalization. CoRR abs/2006.12000 (2020) - [i7]Jooyoung Moon, Jihyo Kim, Younghak Shin, Sangheum Hwang:
Confidence-Aware Learning for Deep Neural Networks. CoRR abs/2007.01458 (2020)
2010 – 2019
- 2018
- [j5]Sangheum Hwang, Myong K. Jeong:
Robust relevance vector machine for classification with variational inference. Ann. Oper. Res. 263(1-2): 21-43 (2018) - [j4]Sangheum Hwang, Dohyun Kim:
A Scalable Feature Based Clustering Algorithm for Sequences with Many Distinct Items. Int. J. Fuzzy Log. Intell. Syst. 18(4): 316-325 (2018) - [i6]Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikaël Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Palhares Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir M. Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric I-Chao Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim:
Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge. CoRR abs/1807.08284 (2018) - 2017
- [c4]Sangheum Hwang, Sunggyun Park:
Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks. DLMIA/ML-CDS@MICCAI 2017: 92-99 - [c3]Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Minsoo Kim:
A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology. DLMIA/ML-CDS@MICCAI 2017: 231-239 - [i5]Sangheum Hwang, Sunggyun Park:
Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks. CoRR abs/1708.00710 (2017) - 2016
- [j3]Sangheum Hwang, Jiho Yoo, Chanhee Lee, Sang Hyun Lee:
Collaborative crystal structure prediction. Expert Syst. Appl. 63: 222-230 (2016) - [j2]Dohyun Kim, Chungmok Lee, Sangheum Hwang, Myong K. Jeong:
A robust support vector regression with a linear-log concave loss function. J. Oper. Res. Soc. 67(5): 735-742 (2016) - [c2]Sangheum Hwang, Hyo-Eun Kim, Jihoon Jeong, Hee-Jin Kim:
A novel approach for tuberculosis screening based on deep convolutional neural networks. Medical Imaging: Computer-Aided Diagnosis 2016: 97852W - [c1]Sangheum Hwang, Hyo-Eun Kim:
Self-Transfer Learning for Weakly Supervised Lesion Localization. MICCAI (2) 2016: 239-246 - [i4]Sangheum Hwang, Hyo-Eun Kim:
Self-Transfer Learning for Fully Weakly Supervised Object Localization. CoRR abs/1602.01625 (2016) - [i3]Hyo-Eun Kim, Sangheum Hwang:
Scale-Invariant Feature Learning using Deconvolutional Neural Networks for Weakly-Supervised Semantic Segmentation. CoRR abs/1602.04984 (2016) - [i2]Hyo-Eun Kim, Sangheum Hwang, Kyunghyun Cho:
Semantic Noise Modeling for Better Representation Learning. CoRR abs/1611.01268 (2016) - [i1]Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Minsoo Kim, Seokhwi Kim:
A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology. CoRR abs/1612.07180 (2016) - 2015
- [j1]Sangheum Hwang, Dohyun Kim, Myong K. Jeong, Bong-Jin Yum:
Robust kernel-based regression with bounded influence for outliers. J. Oper. Res. Soc. 66(8): 1385-1398 (2015)
Coauthor Index
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last updated on 2024-09-22 00:39 CEST by the dblp team
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