213 citations · 792 across the 25 of their papers we have counts for
26 papers
Learning Task-Specific Strategies for Accelerated MRI
Zihui Wu, Tianwei Yin, Yu Sun +4
Compressed sensing magnetic resonance imaging (CS-MRI) seeks to recover visual information from subsampled measurements for diagnostic tasks. Traditional CS-MRI methods often separ…
Coordinate-Based Seismic Interpolation in Irregular Land Survey: A Deep Internal Learning Approach
Paul Goyes, Edwin Vargas, Claudia Correa +4
Physical and budget constraints often result in irregular sampling, which complicates accurate subsurface imaging. Pre-processing approaches, such as missing trace or shot interpol…
Learning Cross-Video Neural Representations for High-Quality Frame Interpolation
Wentao Shangguan, Yu Sun, Weijie Gan +1
This paper considers the problem of temporal video interpolation, where the goal is to synthesize a new video frame given its two neighbors. We propose Cross-Video Neural Represent…
Recovery of Continuous 3D Refractive Index Maps from Discrete Intensity-Only Measurements using Neural Fields
Renhao Liu, Yu Sun, Jiabei Zhu +2
Intensity diffraction tomography (IDT) refers to a class of optical microscopy techniques for imaging the 3D refractive index (RI) distribution of a sample from a set of 2D intensi…
Deformation-Compensated Learning for Image Reconstruction without Ground Truth
Weijie Gan, Yu Sun, Cihat Eldeniz +3
Deep neural networks for medical image reconstruction are traditionally trained using high-quality ground-truth images as training targets. Recent work on Noise2Noise (N2N) has sho…
CoIL: Coordinate-based Internal Learning for Imaging Inverse Problems
Yu Sun, Jiaming Liu, Mingyang Xie +2
We propose Coordinate-based Internal Learning (CoIL) as a new deep-learning (DL) methodology for the continuous representation of measurements. Unlike traditional DL methods that l…