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ORCIDEun Ju Cha
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2020 – today
- 2024
[j8]Eunju Cha:
Regularization by denoising diffusion process meets deep relaxation in phase. Image Vis. Comput. 151: 105282 (2024)- [c5]Soobin Park, Soyoung Na, Seung Hyun Song, Eunju Cha:
Unpaired Training for AFM Image Processing of R2R-Printed CNTs. EUSIPCO 2024: 1841-1845 - [c4]Eunju Cha:
RED-PhaseCut: A Variational Sampler Using Diffusion Model for Fourier Phase Retrieval. EUSIPCO 2024: 1876-1880 - 2022
- [j7]Eunju Cha
, Chanseok Lee, Mooseok Jang, Jong Chul Ye:
DeepPhaseCut: Deep Relaxation in Phase for Unsupervised Fourier Phase Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9931-9943 (2022) - [c3]Minsu Ko, Eunju Cha, Sungjoo Suh, Huijin Lee, Jae-Joon Han, Jinwoo Shin, Bohyung Han:
Self-Supervised Dense Consistency Regularization for Image-to-Image Translation. CVPR 2022: 18280-18289 - 2021
- [j6]Hyungjin Chung, Eunju Cha, Leonard Sunwoo, Jong Chul Ye:
Two-stage deep learning for accelerated 3D time-of-flight MRA without matched training data. Medical Image Anal. 71: 102047 (2021) - [j5]Yoseob Han, Jaeduck Jang, Eunju Cha, Junho Lee, Hyungjin Chung, Myoungho Jeong, Tae-Gon Kim, Byeong Gyu Chae, Hee Goo Kim, Shinae Jun, Sungwoo Hwang, Eunha Lee, Jong Chul Ye:
Deep learning STEM-EDX tomography of nanocrystals. Nat. Mach. Intell. 3(3): 267-274 (2021) - [j4]Eunju Cha, Hyungjin Chung, Eung-Yeop Kim, Jong Chul Ye:
Unpaired Training of Deep Learning tMRA for Flexible Spatio-Temporal Resolution. IEEE Trans. Medical Imaging 40(1): 166-179 (2021) - 2020
- [j3]Mi-Sun Kang, Eunju Cha, Eunhee Kang, Jong Chul Ye, Nam-Gu Her, Jeong-Woo Oh, Do-Hyun Nam, Myoung-Hee Kim, Sejung Yang:
Accuracy improvement of quantification information using super-resolution with convolutional neural network for microscopy images. Biomed. Signal Process. Control. 58: 101846 (2020) - [j2]Eunju Cha, Gyutaek Oh, Jong Chul Ye:
Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction. IEEE J. Sel. Top. Signal Process. 14(6): 1292-1305 (2020) - [i6]Eunju Cha, Gyutaek Oh, Jong Chul Ye:
Geometric Approaches to Increase the Expressivity of Deep Neural Networks for MR Reconstruction. CoRR abs/2003.07740 (2020) - [i5]Eunju Cha, Hyungjin Chung, Eung-Yeop Kim, Jong Chul Ye:
Unsupervised Deep Learning for MR Angiography with Flexible Temporal Resolution. CoRR abs/2003.13096 (2020) - [i4]Hyungjin Chung, Eunju Cha, Leonard Sunwoo, Jong Chul Ye:
Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data. CoRR abs/2008.01362 (2020) - [i3]Eunju Cha, Chanseok Lee, Mooseok Jang, Jong Chul Ye:
DeepPhaseCut: Deep Relaxation in Phase for Unsupervised Fourier Phase Retrieval. CoRR abs/2011.10475 (2020)
2010 – 2019
- 2019
- [i2]Eunju Cha, Jaeduck Jang, Junho Lee, Eunha Lee, Jong Chul Ye:
Boosting CNN beyond Label in Inverse Problems. CoRR abs/1906.07330 (2019) - 2018
- [j1]Jong Chul Ye, Yoseob Han, Eunju Cha:
Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems. SIAM J. Imaging Sci. 11(2): 991-1048 (2018) - [c2]Eunju Cha, Eung-Yeop Kim, Jong Chul Ye:
Improved Time-Resolved MRA Using k-Space Deep Learning. MLMIR@MICCAI 2018: 47-54 - [i1]Eunju Cha, Eung-Yeop Kim, Jong Chul Ye:
k-Space Deep Learning for Parallel MRI: Application to Time-Resolved MR Angiography. CoRR abs/1806.00806 (2018) - 2016
- [c1]Eun Ju Cha, Kyong Hwan Jin, Dongwook Lee, Eung-Yeop Kim, Seung Hong Choi, Jong Chul Ye:
Improved temporal resolution of twist imaging using annihilating filter-based low rank Hankel matrix approach. ISBI 2016: 314-317
Coauthor Index
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