| Ntire 2017 challenge on single image super-resolution: Methods and results R Timofte, E Agustsson, L Van Gool, MH Yang, L Zhang Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1190 | 2017 |
| Stargan v2: Diverse image synthesis for multiple domains Y Choi, Y Uh, J Yoo, JW Ha Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 891 | 2020 |
| Deep learning with domain adaptation for accelerated projection‐reconstruction MR Y Han, J Yoo, HH Kim, HJ Shin, K Sung, JC Ye Magnetic resonance in medicine 80 (3), 1189-1205, 2018 | 287 | 2018 |
| Deep convolutional framelet denosing for low-dose CT via wavelet residual network E Kang, W Chang, J Yoo, JC Ye IEEE transactions on medical imaging 37 (6), 1358-1369, 2018 | 254 | 2018 |
| Deep residual learning for accelerated MRI using magnitude and phase networks D Lee, J Yoo, S Tak, JC Ye IEEE Transactions on Biomedical Engineering 65 (9), 1985-1995, 2018 | 253 | 2018 |
| Photorealistic style transfer via wavelet transforms J Yoo, Y Uh, S Chun, B Kang, JW Ha Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 234 | 2019 |
| Deep residual learning for compressed sensing CT reconstruction via persistent homology analysis YS Han, J Yoo, JC Ye arXiv preprint arXiv:1611.06391, 2016 | 202 | 2016 |
| Beyond deep residual learning for image restoration: Persistent homology-guided manifold simplification W Bae, J Yoo, J Chul Ye Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 161 | 2017 |
| Ntire 2020 challenge on real-world image super-resolution: Methods and results A Lugmayr, M Danelljan, R Timofte Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 135 | 2020 |
| Reliable fidelity and diversity metrics for generative models MF Naeem, SJ Oh, Y Uh, Y Choi, J Yoo International Conference on Machine Learning, 7176-7185, 2020 | 115 | 2020 |
| Rethinking data augmentation for image super-resolution: A comprehensive analysis and a new strategy J Yoo, N Ahn, KA Sohn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 89 | 2020 |
| Time-dependent deep image prior for dynamic MRI J Yoo, KH Jin, H Gupta, J Yerly, M Stuber, M Unser arXiv preprint arXiv:1910.01684, 2019 | 72* | 2019 |
| Deep learning diffuse optical tomography J Yoo, S Sabir, D Heo, KH Kim, A Wahab, Y Choi, SI Lee, EY Chae, ... IEEE transactions on medical imaging 39 (4), 877-887, 2019 | 71 | 2019 |
| Rethinking the truly unsupervised image-to-image translation K Baek, Y Choi, Y Uh, J Yoo, H Shim Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 61 | 2021 |
| Deep artifact learning for compressed sensing and parallel MRI D Lee, J Yoo, JC Ye arXiv preprint arXiv:1703.01120, 2017 | 53 | 2017 |
| Topological persistence vineyard for dynamic functional brain connectivity during resting and gaming stages J Yoo, EY Kim, YM Ahn, JC Ye Journal of neuroscience methods 267, 1-13, 2016 | 40 | 2016 |
| Multi-cryogan: Reconstruction of continuous conformations in cryo-em using generative adversarial networks H Gupta, TH Phan, J Yoo, M Unser Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 23 | 2020 |
| Multi-domain processing via hybrid denoising networks for speech enhancement JH Kim, J Yoo, S Chun, A Kim, JW Ha arXiv preprint arXiv:1812.08914, 2018 | 22 | 2018 |
| Wavelet residual network for low-dose CT via deep convolutional framelets E Kang, J Yoo, JC Ye arXiv preprint arXiv:1707.09938 27, 679-694, 2017 | 17 | 2017 |
| Compressed sensing and parallel MRI using deep residual learning D Lee, J Yoo, JC Ye International Society for Magnetic Resonance in Medicine, 2017 | 15 | 2017 |
Jong Chul YeProfessor and Endowed Chair, KAISTkaist.ac.kr의 이메일 확인됨
