810 results on '"Jong Chul Ye"'
Search Results
202. Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantification.
203. Unsupervised Missing Cone Deep Learning in Optical Diffraction Tomography.
204. DiffusionCLIP: Text-guided Image Manipulation Using Diffusion Models.
205. PyNET-CA: Enhanced PyNET with Channel Attention for End-to-End Mobile Image Signal Processing.
206. Score-based diffusion models for accelerated MRI.
207. Multi-task vision transformer using low-level chest X-ray feature corpus for COVID-19 diagnosis and severity quantification.
208. Unsupervised resolution-agnostic quantitative susceptibility mapping using adaptive instance normalization.
209. Deep residual learning for compressed sensing MRI.
210. NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results.
211. Beyond Deep Residual Learning for Image Restoration: Persistent Homology-Guided Manifold Simplification.
212. Switchable Deep Beamformer.
213. Continuous Conversion of CT Kernel using Switchable CycleGAN with AdaIN.
214. OT-driven Multi-Domain Unsupervised Ultrasound Image Artifact Removal using a Single CNN.
215. Unsupervised CT Metal Artifact Learning using Attention-guided beta-CycleGAN.
216. AdaIN-Switchable CycleGAN for Efficient Unsupervised Low-Dose CT Denoising.
217. Unsupervised MR Motion Artifact Deep Learning using Outlier-Rejecting Bootstrap Aggregation.
218. Understanding Graph Isomorphism Network for Brain MR Functional Connectivity Analysis.
219. Unsupervised Denoising for Satellite Imagery using Wavelet Subband CycleGAN.
220. CycleQSM: Unsupervised QSM Deep Learning using Physics-Informed CycleGAN.
221. CycleMorph: Cycle Consistent Unsupervised Deformable Image Registration.
222. Unsupervised Deep Learning for MR Angiography with Flexible Temporal Resolution.
223. Two-Stage Deep Learning for Accelerated 3D Time-of-Flight MRA without Matched Training Data.
224. DeepPhaseCut: Deep Relaxation in Phase for Unsupervised Fourier Phase Retrieval.
225. Pushing the Limit of Unsupervised Learning for Ultrasound Image Artifact Removal.
226. Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems.
227. Unified Theory for Recovery of Sparse Signals in a General Transform Domain.
228. Image Reconstruction is a New Frontier of Machine Learning.
229. Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT.
230. Deep Convolutional Framelet Denosing for Low-Dose CT via Wavelet Residual Network.
231. A Mathematical Framework for Deep Learning in Elastic Source Imaging.
232. Deep Residual Learning for Accelerated MRI Using Magnitude and Phase Networks.
233. Grid-Free Localization Algorithm Using Low-Rank Hankel Matrix for Super-Resolution Microscopy.
234. Sparse and Low-Rank Decomposition of a Hankel Structured Matrix for Impulse Noise Removal.
235. Enhanced Diagnosis of Plaque Erosion by Deep Learning in Patients With Acute Coronary Syndromes
236. Reference-free EPI Nyquist ghost correction using annihilating filter-based low rank hankel matrix for K-space interpolation.
237. Compressive dynamic aperture B-mode ultrasound imaging using annihilating filter-based low-rank interpolation.
238. Sparse and low-rank decomposition of MR artifact images using annihilating filter-based Hankel matrix.
239. Sparse-view X-ray spectral CT reconstruction using annihilating filter-based low rank hankel matrix approach.
240. Improved temporal resolution of twist imaging using annihilating filter-based low rank Hankel matrix approach.
241. Random impulse noise removal using sparse and low rank decomposition of annihilating filter-based Hankel matrix.
242. Recent progresses of accelerated MRI using annihilating filter-based low-rank interpolation.
243. A Joint Sparse Recovery Framework for Accurate Reconstruction of Inclusions in Elastic Media.
244. Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation.
245. Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal.
246. Boosting CNN beyond Label in Inverse Problems.
247. Multiphase Level-Set Loss for Semi-Supervised and Unsupervised Segmentation with Deep Learning.
248. Optimal Transport, CycleGAN, and Penalized LS for Unsupervised Learning in Inverse Problems.
249. CycleGAN with a Blur Kernel for Deconvolution Microscopy: Optimal Transport Geometry.
250. Which Contrast Does Matter? Towards a Deep Understanding of MR Contrast using Collaborative GAN.
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