| 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 | 486 | 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 | 284 | 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 | 230 | 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 | 199* | 2021 |
| Self-transfer learning for weakly supervised lesion localization S Hwang, HE Kim Medical Image Computing and Computer-Assisted Intervention–MICCAI 2016: 19th …, 2016 | 179* | 2016 |
| Confidence-aware learning for deep neural networks J Moon, J Kim, Y Shin, S Hwang International Conference on Machine Learning, 7034-7044, 2020 | 140 | 2020 |
| 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 | 69 | 2017 |
| BERT-based Classification Model for Korean Documents S Hwang, D Kim Journal of Society for e-Business Studies 25 (1), 2020 | 51* | 2020 |
| 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 | 51 | 2017 |
| Deconvolutional feature stacking for weakly-supervised semantic segmentation HE Kim, S Hwang arXiv preprint arXiv:1602.04984, 2016 | 40* | 2016 |
| Object recognition method and apparatus based on weakly supervised learning HE Kim, SH Hwang US Patent 10,102,444, 2018 | 32 | 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 | 29 | 2013 |
| 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 |
| 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 unified benchmark for the unknown detection capability of deep neural networks J Kim, J Koo, S Hwang Expert Systems with Applications 229, 120461, 2023 | 14 | 2023 |
| Quantum efficiency affected by localized carrier distribution near the V-defect in GaN based quantum well YH Cho, JY Kim, J Kim, MB Shim, S Hwang, SH Park, YS Park, S Kim Applied Physics Letters 103 (26), 2013 | 14 | 2013 |
| A New Splitting Criterion for Better Interpretable Trees S Hwang, HG Yeo, JS Hong IEEE Access 8, 62762-62774, 2020 | 13 | 2020 |
| Robust relevance vector machine for classification with variational inference S Hwang, MK Jeong Annals of Operations Research 263, 21-43, 2018 | 11 | 2018 |
| A new smart smudge attack using CNN H Shin, S Sim, H Kwon, S Hwang, Y Lee International Journal of Information Security, 1-12, 2022 | 10 | 2022 |
| Classification apparatus for pathologic diagnosis of medical image, and pathologic diagnosis system using the same HE Kim, S Hwang, P Seung-Wook, JI Lee, J Min-Hong, YOO Dong-Geun, ... US Patent 10,013,757, 2018 | 9 | 2018 |
Hyo-Eun KimRebellions Inc.Verified email at rebellions.ai
