| Momentum-Net: Fast and convergent iterative neural network for inverse problems IY Chun, Z Huang, H Lim, J Fessler IEEE transactions on pattern analysis and machine intelligence, 2023 | 105 | 2023 |
| Ranging and light field imaging with transparent photodetectors MB Lien, CH Liu, IY Chun, S Ravishankar, H Nien, M Zhou, JA Fessler, ... Nature Photonics 14 (3), 143-148, 2020 | 88 | 2020 |
| Convolutional dictionary learning: Acceleration and convergence IY Chun, JA Fessler IEEE Transactions on Image Processing 27 (4), 1697-1712, 2017 | 87 | 2017 |
| DTI detection of longitudinal WM abnormalities due to accumulated head impacts IY Chun, X Mao, EL Breedlove, LJ Leverenz, EA Nauman, TM Talavage Developmental neuropsychology 40 (2), 92-97, 2015 | 74 | 2015 |
| Improved low-count quantitative PET reconstruction with an iterative neural network H Lim, IY Chun, YK Dewaraja, JA Fessler IEEE Transactions on Medical Imaging, 2020 | 63 | 2020 |
| Deep BCD-Net Using Identical Encoding-Decoding CNN Structures for Iterative Image Recovery IY Chun, JA Fessler 2018 IEEE 13th Image, Video, and Multidimensional Signal Processing Workshop …, 2018 | 63 | 2018 |
| Convolutional analysis operator learning: Acceleration and convergence IY Chun, JA Fessler IEEE Transactions on Image Processing, 2019 | 58 | 2019 |
| Efficient Compressed Sensing SENSE pMRI Reconstruction with Joint Sparsity Promotion IY Chun, B Adcock, T Talavage Medical Imaging, IEEE Transactions on 35 (1), 354-368, 2015 | 54 | 2015 |
| Compressed sensing and parallel acquisition IY Chun, B Adcock IEEE Transactions on Information Theory 63 (8), 4860-4882, 2017 | 43 | 2017 |
| Every hit matters: white matter diffusivity changes in high school football athletes are correlated with repetitive head acceleration event exposure I Jang, IY Chun, JR Brosch, S Bari, Y Zou, BR Cummiskey, TA Lee, ... Neuroimage: clinical 24, 101930, 2019 | 39 | 2019 |
| BCD-Net for low-dose CT reconstruction: Acceleration, convergence, and generalization IY Chun, X Zheng, Y Long, JA Fessler Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 37 | 2019 |
| Sparse-View X-Ray CT Reconstruction Using l1 Regularization with Learned Sparsifying Transform IY Chun, X Zheng, Long, Yong, JA Fessler 14th International Meeting on Fully Three-Dimensional Image Reconstruction …, 2017 | 24 | 2017 |
| Neural network based 3D tracking with a graphene transparent focal stack imaging system D Zhang, Z Xu, Z Huang, AR Gutierrez, CJ Blocker, CH Liu, MB Lien, ... Nature Communications 12 (1), 2413, 2021 | 22 | 2021 |
| Physics-driven deep training of dictionary-based algorithms for MR image reconstruction S Ravishankar, IY Chun, JA Fessler 2017 51st Asilomar Conference on Signals, Systems, and Computers, 1859-1863, 2017 | 20 | 2017 |
| Convolutional analysis operator learning: Dependence on training data IY Chun, D Hong, B Adcock, JA Fessler IEEE signal processing letters 26 (8), 1137-1141, 2019 | 18 | 2019 |
| Sparse-View X-Ray CT Reconstruction Using Prior with Learned Transform X Zheng, IY Chun, Z Li, Y Long, JA Fessler arXiv preprint arXiv:1711.00905, 2017 | 17 | 2017 |
| Low-Rank Plus Sparse Tensor Models for Light-field Reconstruction from Focal Stack Data CJ Blocker, IY Chun, JA Fessler 2018 IEEE 13th Image, Video, and Multidimensional Signal Processing Workshop …, 2018 | 15 | 2018 |
| Efficient compressed sensing statistical X-ray/CT reconstruction from fewer measurements IY Chun, TM Talavage 12th International Meeting on Fully Three-Dimensional Image Reconstruction …, 2013 | 14 | 2013 |
| Convolutional analysis operator learning: Application to sparse-view CT IY Chun, JA Fessler 2018 52nd Asilomar Conference on Signals, Systems, and Computers, 1631-1635, 2018 | 13 | 2018 |
| Convergent convolutional dictionary learning using adaptive contrast enhancement (CDL-ACE): Application of CDL to image denoising IY Chun, JA Fessler 2017 International Conference on Sampling Theory and Applications (SampTA …, 2017 | 13 | 2017 |
Jeff FesslerProfessor of Electrical Engineering and Computer Science, Univ. of Michigan在 umich.edu 的电子邮件经过验证
