| Deep convolutional framelets: A general deep learning framework for inverse problems JC Ye, Y Han, E Cha SIAM Journal on Imaging Sciences 11 (2), 991-1048, 2018 | 383 | 2018 |
| Deep learning STEM-EDX tomography of nanocrystals Y Han, J Jang, E Cha, J Lee, H Chung, M Jeong, TG Kim, BG Chae, ... Nature Machine Intelligence 3 (3), 267-274, 2021 | 33 | 2021 |
| Deepphasecut: Deep relaxation in phase for unsupervised fourier phase retrieval E Cha, C Lee, M Jang, JC Ye IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (12), 9931 …, 2021 | 19 | 2021 |
| Two-stage deep learning for accelerated 3D time-of-flight MRA without matched training data H Chung, E Cha, L Sunwoo, JC Ye Medical Image Analysis 71, 102047, 2021 | 19 | 2021 |
| Self-supervised dense consistency regularization for image-to-image translation M Ko, E Cha, S Suh, H Lee, JJ Han, J Shin, B Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 18 | 2022 |
| Unpaired training of deep learning tMRA for flexible spatio-temporal resolution E Cha, H Chung, EY Kim, JC Ye IEEE Transactions on Medical Imaging 40 (1), 166-179, 2020 | 18 | 2020 |
| Accuracy improvement of quantification information using super-resolution with convolutional neural network for microscopy images MS Kang, E Cha, E Kang, JC Ye, NG Her, JW Oh, DH Nam, MH Kim, ... Biomedical Signal Processing and Control 58, 101846, 2020 | 18 | 2020 |
| Geometric approaches to increase the expressivity of deep neural networks for MR reconstruction E Cha, G Oh, JC Ye IEEE Journal of Selected Topics in Signal Processing 14 (6), 1292-1305, 2020 | 15 | 2020 |
| Boosting CNN beyond label in inverse problems E Cha, J Jang, J Lee, E Lee, JC Ye arXiv preprint arXiv:1906.07330, 2019 | 7 | 2019 |
| Low-dose sparse-view HAADF-STEM-EDX tomography of nanocrystals using unsupervised deep learning E Cha, H Chung, J Jang, J Lee, E Lee, JC Ye ACS nano 16 (7), 10314-10326, 2022 | 6 | 2022 |
| True temporal resolution TWIST imaging using annihilating filter-based low-rank wrap around Hankel matrix E Cha, KH Jin, EY Kim, JC Ye The International Society for Magnetic Resonance in Medicine. ISMRM, 2017 | 4 | 2017 |
| K-space deep learning for parallel MRI: application to time-resolved MR angiography E Cha, EY Kim, JC Ye arXiv preprint arXiv:1806.00806, 2018 | 3 | 2018 |
| Improved Time-Resolved MRA Using k-Space Deep Learning E Cha, EY Kim, JC Ye International Workshop on Machine Learning for Medical Image Reconstruction …, 2018 | 2 | 2018 |
| Unsupervised Deep Learning for MR Angiography with Flexible Temporal Resolution E Cha, H Chung, EY Kim, JC Ye arXiv preprint arXiv:2003.13096, 2020 | | 2020 |
| Apparatus and method for reconstructing image using extended neural network E Cha, YS Han, JC Ye US, 2018 | | 2018 |
| Improved temporal resolution of twist imaging using annihilating filter-based low rank Hankel matrix approach EJ Cha, KH Jin, D Lee, EY Kim, SH Choi, JC Ye 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), 314-317, 2016 | | 2016 |
| Improved Temporal Resolution TWIST Reconstruction using annihilating filter-based low rank Hankel matrix (ALOHA) EJ Cha, KH Jin, D Lee, EY Kim, SH Choi, JC Ye International Society for Magnetic Resonance in Medicine 2016, 2016 | | 2016 |
| Self-Supervised Dense Consistency Regularization for Image-to-Image Translation Supplementary Document M Ko, E Cha, S Suh, H Lee, JJ Han, J Shin, B Han | | |
| Improved TWIST Imaging using k-Space Deep Learning E Cha, EY Kim, JC Ye | | |
| Improved Temporal Resolution TWIST Reconstruction using Annihilating Filter-based Low-rank Hankel Matrix EJ Cha, KH Jin, DW Lee, EY Kim, SH Choi, JC Ye | | |
Jong Chul YeProfessor and Endowed Chair, KAIST在 kaist.ac.kr 的电子邮件经过验证
