Jong Chul Ye
Jong Chul Ye
Professor and Endowed Chair, KAIST
Verified email at - Homepage
Cited by
Cited by
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
NIRS-SPM: statistical parametric mapping for near-infrared spectroscopy
JC Ye, S Tak, KE Jang, J Jung, J Jang
Neuroimage 44 (2), 428-447, 2009
Deep learning COVID-19 features on CXR using limited training data sets
Y Oh, S Park, JC Ye
IEEE transactions on medical imaging 39 (8), 2688-2700, 2020
A deep convolutional neural network using directional wavelets for low‐dose X‐ray CT reconstruction
E Kang, J Min, JC Ye
Medical physics 44 (10), e360-e375, 2017
k‐t FOCUSS: a general compressed sensing framework for high resolution dynamic MRI
H Jung, K Sung, KS Nayak, EY Kim, JC Ye
Magnetic Resonance in Medicine: An Official Journal of the International …, 2009
Geometric gan
JH Lim, JC Ye
arXiv preprint arXiv:1705.02894, 2017
Framing U-Net via deep convolutional framelets: Application to sparse-view CT
Y Han, JC Ye
IEEE transactions on medical imaging 37 (6), 1418-1429, 2018
Diffusionclip: Text-guided diffusion models for robust image manipulation
G Kim, T Kwon, JC Ye
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022
Image reconstruction is a new frontier of machine learning
G Wang, JC Ye, K Mueller, JA Fessler
IEEE transactions on medical imaging 37 (6), 1289-1296, 2018
Statistical analysis of fNIRS data: a comprehensive review
S Tak, JC Ye
Neuroimage 85, 72-91, 2014
Deep learning for tomographic image reconstruction
G Wang, JC Ye, B De Man
Nature machine intelligence 2 (12), 737-748, 2020
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
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
Diffusion posterior sampling for general noisy inverse problems
H Chung, J Kim, MT Mccann, ML Klasky, JC Ye
arXiv preprint arXiv:2209.14687, 2022
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
Improved k–t BLAST and k–t SENSE using FOCUSS
H Jung, JC Ye, EY Kim
Physics in Medicine & Biology 52 (11), 3201, 2007
-Space Deep Learning for Accelerated MRI
Y Han, L Sunwoo, JC Ye
IEEE transactions on medical imaging 39 (2), 377-386, 2019
Compressive MUSIC: Revisiting the link between compressive sensing and array signal processing
JM Kim, OK Lee, JC Ye
IEEE Transactions on Information Theory 58 (1), 278-301, 2012
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
A general framework for compressed sensing and parallel MRI using annihilating filter based low-rank Hankel matrix
KH Jin, D Lee, JC Ye
IEEE Transactions on Computational Imaging 2 (4), 480-495, 2016
The system can't perform the operation now. Try again later.
Articles 1–20