| Development and validation of deep learning–based automatic detection algorithm for malignant pulmonary nodules on chest radiographs JG Nam, S Park, EJ Hwang, JH Lee, KN Jin, KY Lim, TH Vu, JH Sohn, ... Radiology 290 (1), 218-228, 2019 | 512 | 2019 |
| Predicting breast tumor proliferation from whole-slide images: the TUPAC16 challenge M Veta, YJ Heng, N Stathonikos, BE Bejnordi, F Beca, T Wollmann, ... Medical image analysis 54, 111-121, 2019 | 298 | 2019 |
| A novel approach for tuberculosis screening based on deep convolutional neural networks S Hwang, HE Kim, J Jeong, HJ Kim Medical imaging 2016: computer-aided diagnosis 9785, 750-757, 2016 | 238 | 2016 |
| Self-knowledge distillation with progressive refinement of targets K Kim, BM Ji, D Yoon, S Hwang Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 175 | 2021 |
| Confidence-aware learning for deep neural networks J Moon, J Kim, Y Shin, S Hwang International Conference on Machine Learning, 7034-7044, 2020 | 156 | 2020 |
| Self-transfer learning for weakly supervised lesion localization S Hwang, HE Kim Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 124 | 2016 |
| A unified framework for tumor proliferation score prediction in breast histopathology K Paeng, S Hwang, S Park, M Kim Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017 | 71 | 2017 |
| Self-transfer learning for fully weakly supervised object localization S Hwang, HE Kim arXiv preprint arXiv:1602.01625, 2016 | 57 | 2016 |
| Accurate lung segmentation via network-wise training of convolutional networks S Hwang, S Park Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical …, 2017 | 53 | 2017 |
| Self-knowledge distillation: A simple way for better generalization K Kim, BM Ji, D Yoon, S Hwang arXiv preprint arXiv:2006.12000 3, 1, 2020 | 51 | 2020 |
| Object recognition method and apparatus based on weakly supervised learning HE Kim, SH Hwang US Patent 10,102,444, 2018 | 34 | 2018 |
| Robust relevance vector machine with variational inference for improving virtual metrology accuracy S Hwang, MK Jeong, BJ Yum IEEE Transactions on Semiconductor Manufacturing 27 (1), 83-94, 2013 | 30 | 2013 |
| BERT-based classification model for Korean documents S Hwang, D Kim Journal of Society for e-Business Studies 25 (1), 2020 | 29 | 2020 |
| 한국어 기술문서 분석을 위한 BERT 기반의 분류모델 황상흠， 김도현 한국전자거래학회지 25 (1), 203-214, 2020 | 24 | 2020 |
| Deconvolutional feature stacking for weakly-supervised semantic segmentation HE Kim, S Hwang arXiv preprint arXiv:1602.04984, 2016 | 23 | 2016 |
| Cloud-based pathological analysis system and method HE Kim, S Hwang, P Seung-Wook, JI Lee, J Min-Hong, YOO Dong-Geun, ... US Patent App. 15/113,680, 2017 | 19 | 2017 |
| Scale-invariant feature learning using deconvolutional neural networks for weakly-supervised semantic segmentation H Kim, S Hwang arXiv preprint arXiv:1602.04984, 2016 | 18 | 2016 |
| A unified benchmark for the unknown detection capability of deep neural networks J Kim, J Koo, S Hwang Expert Systems with Applications 229, 120461, 2023 | 17 | 2023 |
| A unified framework for tumor proliferation score prediction in breast histopathology K Paeng, S Hwang, S Park, M Kim arXiv preprint arXiv:1612.07180, 2016 | 16 | 2016 |
| A New Splitting Criterion for Better Interpretable Trees S Hwang, HG Yeo, JS Hong IEEE Access 8, 62762-62774, 2020 | 15 | 2020 |
Hyo-Eun KimRebellions Inc.在 rebellions.ai 的电子邮件经过验证
