Sangheum Hwang

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 38

Top Topics

Relevance Vector Machine

Transfer Learning

Weakly Supervised

Medical Image Segmentation

Top Venues

DLMIA/ML-CDS@MICCAI

J. Oper. Res. Soc.

Publications

SeokHyun Seo, Jinwoo Hong, Jungwoo Chae, Kyungyul Kim, Sangheum Hwang
GTA: Guided Transfer of Spatial Attention from Object-Centric Representations. CoRR (2024)
Seungwon Seo, Suho Lee, Sangheum Hwang
StochCA: A Novel Approach for Exploiting Pretrained Models with Cross-Attention. CoRR (2024)
Jiin Koo, Sungjoon Choi, Sangheum Hwang
Generalized Outlier Exposure: Towards a trustworthy out-of-distribution detector without sacrificing accuracy. Neurocomputing 577 (2024)
Jeonghyeon Kim, Jihyo Kim, Sangheum Hwang
Comparison of Out-of-Distribution Detection Performance of CLIP-based Fine-Tuning Methods. ICEIC (2024)
Soojin Lee, Sangheum Hwang
Context-aware cross feature attentive network for click-through rate predictions. Appl. Intell. 54 (19) (2024)
Carlos Vintimilla, Sangheum Hwang
Self-Supervised Representation Learning for Basecalling Nanopore Sequencing Data. IEEE Access 12 (2024)
Suho Lee, Seungwon Seo, Jihyo Kim, Yejin Lee, Sangheum Hwang
Few-shot Fine-tuning is All You Need for Source-free Domain Adaptation. CoRR (2023)
Jae-Hun Lee, Doyoung Yoon, Byeongmoon Ji, Kyungyul Kim, Sangheum Hwang
Rethinking Evaluation Protocols of Visual Representations Learned via Self-supervised Learning. CoRR (2023)
Jihyo Kim, Jiin Koo, Sangheum Hwang
A unified benchmark for the unknown detection capability of deep neural networks. Expert Syst. Appl. 229 (Part A) (2023)
Jihyo Kim, Jeonghyeon Kim, Sangheum Hwang
Deep Active Learning with Contrastive Learning Under Realistic Data Pool Assumptions. CoRR (2023)
Jeongeun Park, Seungyoun Shin, Sangheum Hwang, Sungjoon Choi
Elucidating robust learning with uncertainty-aware corruption pattern estimation. Pattern Recognit. 138 (2023)
Hansub Shin, Sungyong Sim, Hyukyoon Kwon, Sangheum Hwang, Younho Lee
A new smart smudge attack using CNN. Int. J. Inf. Sec. 21 (1) (2022)
Jaemoon Hwang, Sangheum Hwang
Exploiting Global Structure Information to Improve Medical Image Segmentation. Sensors 21 (9) (2021)
Jihyo Kim, Jiin Koo, Sangheum Hwang
A Unified Benchmark for the Unknown Detection Capability of Deep Neural Networks. CoRR (2021)
Seungyeon Lee, Eunji Jo, Sangheum Hwang, Gyeong Bok Jung, Dohyun Kim
Similarity based Deep Neural Networks. Int. J. Fuzzy Log. Intell. Syst. 21 (3) (2021)
Jaehoon Koo, Sangheum Hwang
A Unified Defect Pattern Analysis of Wafer Maps Using Density-Based Clustering. IEEE Access 9 (2021)
Sangwoo Lee, Yejin Lee, Geongyu Lee, Sangheum Hwang
Supervised Contrastive Embedding for Medical Image Segmentation. IEEE Access 9 (2021)
Kyungyul Kim, Byeongmoon Ji, Doyoung Yoon, Sangheum Hwang
Self-Knowledge Distillation with Progressive Refinement of Targets. ICCV (2021)
Jeongeun Park, Seungyoun Shin, Sangheum Hwang, Sungjoon Choi
Elucidating Noisy Data via Uncertainty-Aware Robust Learning. CoRR (2021)
Sangheum Hwang, Hyeon Gyu Yeo, Jung-Sik Hong
A New Splitting Criterion for Better Interpretable Trees. IEEE Access 8 (2020)
Jooyoung Moon, Jihyo Kim, Younghak Shin, Sangheum Hwang
Confidence-Aware Learning for Deep Neural Networks. CoRR (2020)
Minyoung Park, Seungyeon Lee, Sangheum Hwang, Dohyun Kim
Additive Ensemble Neural Networks. IEEE Access 8 (2020)
Kyungyul Kim, Byeongmoon Ji, Doyoung Yoon, Sangheum Hwang
Self-Knowledge Distillation: A Simple Way for Better Generalization. CoRR (2020)
Jooyoung Moon, Jihyo Kim, Younghak Shin, Sangheum Hwang
Confidence-Aware Learning for Deep Neural Networks. ICML (2020)
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 (2018)
Sangheum Hwang, Myong K. Jeong
Robust relevance vector machine for classification with variational inference. Ann. Oper. Res. 263 (1-2) (2018)
Sangheum Hwang, Dohyun Kim
A Scalable Feature Based Clustering Algorithm for Sequences with Many Distinct Items. Int. J. Fuzzy Log. Intell. Syst. 18 (4) (2018)
Sangheum Hwang, Sunggyun Park
Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks. DLMIA/ML-CDS@MICCAI (2017)
Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Minsoo Kim
A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology. DLMIA/ML-CDS@MICCAI (2017)
Sangheum Hwang, Sunggyun Park
Accurate Lung Segmentation via Network-Wise Training of Convolutional Networks. CoRR (2017)
Sangheum Hwang, Hyo-Eun Kim
Self-Transfer Learning for Fully Weakly Supervised Object Localization. CoRR (2016)
Hyo-Eun Kim, Sangheum Hwang, Kyunghyun Cho
Semantic Noise Modeling for Better Representation Learning. CoRR (2016)
Sangheum Hwang, Jiho Yoo, Chanhee Lee, Sang Hyun Lee
Collaborative crystal structure prediction. Expert Syst. Appl. 63 (2016)
Sangheum Hwang, Hyo-Eun Kim
Self-Transfer Learning for Weakly Supervised Lesion Localization. MICCAI (2) (2016)
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) (2016)
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)
Hyo-Eun Kim, Sangheum Hwang
Scale-Invariant Feature Learning using Deconvolutional Neural Networks for Weakly-Supervised Semantic Segmentation. CoRR (2016)
Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Minsoo Kim, Seokhwi Kim
A Unified Framework for Tumor Proliferation Score Prediction in Breast Histopathology. CoRR (2016)
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) (2015)