| Better to Follow, Follow to Be Better: Towards Precise Supervision of Feature Super-Resolution for Small Object Detection J Noh, W Bae, W Lee, J Seo, G Kim IEEE International Conference on Computer Vision (ICCV), 9725-9734, 2019 | 241 | 2019 |
| A Machine Learning Approach Using Survival Statistics to Predict Graft Survival in Kidney Transplant Recipients: A Multicenter Cohort Study KD Yoo, J Noh, H Lee, DK Kim, CS Lim, YH Kim, JP Lee, G Kim, YS Kim Scientific reports 7 (1), 1-12, 2017 | 132 | 2017 |
| Rethinking Class Activation Mapping for Weakly Supervised Object Localization W Bae, J Noh, G Kim European Conference on Computer Vision (ECCV), 2020 | 129 | 2020 |
| Improving Occlusion and Hard Negative Handling for Single-Stage Pedestrian Detectors J Noh, S Lee, B Kim, G Kim IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 966-974, 2018 | 107 | 2018 |
| Superior Outcomes of Kidney Transplantation Compared with Dialysis: An Optimal Matched Analysis of a National Population-based Cohort Study between 2005 and 2008 in Korea KD Yoo, CT Kim, MH Kim, J Noh, G Kim, H Kim, JN An, JY Park, H Cho, ... Medicine 95 (33), 2016 | 72 | 2016 |
| Stable Forecasting of Environmental Time Series via Long Short Term Memory Recurrent Neural Network K Kim, DK Kim, J Noh, M Kim IEEE Access 6, 75216-75228, 2018 | 62 | 2018 |
| Object Discovery via Contrastive Learning for Weakly Supervised Object Detection J Seo, W Bae, DJ Sutherland, J Noh, D Kim European Conference on Computer Vision (ECCV), 312-329, 2022 | 33 | 2022 |
| Prediction of the Mortality Risk in Peritoneal Dialysis Patients using Machine Learning Models: A Nation-wide Prospective Cohort in Korea J Noh, KD Yoo, W Bae, JS Lee, K Kim, JH Cho, H Lee, DK Kim, CS Lim, ... Scientific Reports 10 (1), 1-11, 2020 | 30 | 2020 |
| Estimating Multiple Evoked Emotions from Videos W Choe, HS Chun, J Noh, SD Lee, BT Zhang Proceedings of the Annual Meeting of the Cognitive Science Society (CogSci …, 2013 | 18 | 2013 |
| Recalibration and Validation of the Charlson Comorbidity Index in an Asian Population: the National Health Insurance Service-National Sample Cohort Study JS Choi, MH Kim, YC Kim, YH Lim, HJ Bae, DK Kim, JY Park, J Noh, ... Scientific Reports 10 (1), 1-10, 2020 | 16 | 2020 |
| Line Chart Understanding with Convolutional Neural Network C Sohn, H Choi, K Kim, J Park, J Noh Electronics 10 (6), 749, 2021 | 13 | 2021 |
| Tackling the Challenges in Scene Graph Generation With Local-to-Global Interactions S Woo, J Noh, K Kim IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022 | 11 | 2022 |
| What and when to look?: Temporal span proposal network for video visual relation detection S Woo, J Noh, K Kim arXiv preprint arXiv:2107.07154, 2021 | 9 | 2021 |
| One Weird Trick to Improve Your Semi-Weakly Supervised Semantic Segmentation Model W Bae, J Noh, MJ Asadabadi, DJ Sutherland International Joint Conference on Artificial Intelligence (IJCAI), 2805-2811, 2022 | 5 | 2022 |
| Predicting Outcomes of Continuous Renal Replacement Therapy using Body Composition Monitoring: A Deep-Learning Approach KD Yoo, J Noh, W Bae, JN An, HJ Oh, H Rhee, EY Seong, SH Baek, ... Scientific Reports 13 (1), 4605, 2023 | 4 | 2023 |
| LID 2020: The learning from imperfect data challenge results Y Wei, S Zheng, MM Cheng, H Zhao, L Wang, E Ding, Y Yang, A Torralba, ... arXiv preprint arXiv:2010.11724, 2020 | 3 | 2020 |
| Robust Detection for Autonomous Elevator Boarding Using a Mobile Manipulator S Shin, JH Lee, J Noh, S Choi Asian Conference on Pattern Recognition, 15-28, 2023 | 2 | 2023 |
| Prediction of the Clinical Outcomes in Patients with CRRT Using Body Composition Monitoring: A Machine Learning Approach to a Multicenter Cohort Study: PO0251 KD Yoo, J Noh, JN An, SH Baek, SY Ahn, H Rhee, EY Seong, JH Cho, ... Journal of the American Society of Nephrology 32 (10S), 129-130, 2021 | 2 | 2021 |
| What and when to look?: Temporal span proposal network for video relation detection S Woo, J Noh, K Kim arXiv preprint arXiv:2107.07154, 2021 | 2 | 2021 |
| Revisiting Class Activation Mapping for Learning from Imperfect Data W Bae, J Noh, J Seo, G Kim The 2020 Learning from Imperfect Data (LID) Challenge - CVPR Workshops, 2020 | 2 | 2020 |
Wonho BaeUniversity of British Columbia, VancouverVerified email at cs.ubc.ca
