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July 2020 |
Momentum-Net: Fast and convergent iterative neural network for inverse problems
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January 2020 |
Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms
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October 2020 |
MoDL: Model-Based Deep Learning Architecture for Inverse Problems
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February 2019 |
NeRF
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January 2022 |
SGD-Net: Efficient Model-Based Deep Learning With Theoretical Guarantees
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January 2021 |
Memory-Efficient Learning for Large-Scale Computational Imaging
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January 2020 |
J-MoDL: Joint Model-Based Deep Learning for Optimized Sampling and Reconstruction
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October 2020 |
Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic Tomography
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June 2018 |
Learned Primal-Dual Reconstruction
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June 2018 |
Plug-and-Play ADMM for Image Restoration: Fixed-Point Convergence and Applications
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March 2017 |
Plug-and-Play Unplugged: Optimization-Free Reconstruction Using Consensus Equilibrium
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January 2018 |
Provable Convergence of Plug-and-Play Priors With MMSE Denoisers
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January 2020 |
An Online Plug-and-Play Algorithm for Regularized Image Reconstruction
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September 2019 |
Solving ill-posed inverse problems using iterative deep neural networks
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November 2017 |
ISTA-Net: Interpretable Optimization-Inspired Deep Network for Image Compressive Sensing
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conference
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June 2018 |
Block Coordinate Regularization by Denoising
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January 2020 |
FFDNet: Toward a Fast and Flexible Solution for CNN-Based Image Denoising
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September 2018 |
A New Recurrent Plug-and-Play Prior Based on the Multiple Self-Similarity Network
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January 2020 |
A Convergent Image Fusion Algorithm Using Scene-Adapted Gaussian-Mixture-Based Denoising
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January 2019 |
Image Restoration by Iterative Denoising and Backward Projections
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March 2019 |
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems
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conference
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October 2017 |
Plug-and-Play Methods for Magnetic Resonance Imaging: Using Denoisers for Image Recovery
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journal
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January 2020 |
Deep Plug-And-Play Super-Resolution for Arbitrary Blur Kernels
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conference
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June 2019 |
Regularized Fourier Ptychography Using an Online Plug-and-play Algorithm
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conference
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May 2019 |
Learning Deep CNN Denoiser Prior for Image Restoration
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conference
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July 2017 |
Plug-and-Play Priors for Bright Field Electron Tomography and Sparse Interpolation
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January 2016 |
BM3D Frames and Variational Image Deblurring
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April 2012 |
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
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January 2006 |
Using Deep Neural Networks for Inverse Problems in Imaging: Beyond Analytical Methods
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January 2018 |
Convolutional Neural Networks for Inverse Problems in Imaging: A Review
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November 2017 |
Deep learning for tomographic image reconstruction
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December 2020 |
Deep Learning Techniques for Inverse Problems in Imaging
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May 2020 |
Deep Convolutional Neural Network for Inverse Problems in Imaging
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September 2017 |
Proximité et dualité dans un espace hilbertien
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January 1951 |
Image reconstruction by domain-transform manifold learning
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March 2018 |
Deep Learning Computed Tomography: Learning Projection-Domain Weights From Image Domain in Limited Angle Problems
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June 2018 |
A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
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January 2009 |
Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
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January 2011 |
A dual algorithm for the solution of nonlinear variational problems via finite element approximation
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January 1976 |
Deep-Neural-Network-Based Sinogram Synthesis for Sparse-View CT Image Reconstruction
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March 2019 |
Fast Enhanced CT Metal Artifact Reduction Using Data Domain Deep Learning
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January 2020 |
Data and Image Prior Integration for Image Reconstruction Using Consensus Equilibrium
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January 2021 |
${k}$ -Space Deep Learning for Accelerated MRI
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February 2020 |
Regularization by Denoising: Clarifications and New Interpretations
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March 2019 |
Regularization by Denoising via Fixed-Point Projection (RED-PRO)
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January 2021 |
Dynamic MRI using model‐based deep learning and SToRM priors: MoDL‐SToRM
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journal
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March 2019 |
Solving Linear Inverse Problems Using Gan Priors: An Algorithm with Provable Guarantees
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conference
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April 2018 |
Wavelet-based image estimation: an empirical Bayes approach using Jeffrey's noninformative prior
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January 2001 |
Nonlinear total variation based noise removal algorithms
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November 1992 |
Multilayer feedforward networks are universal approximators
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January 1989 |
Versatile reconstruction framework for diffraction tomography with intensity measurements and multiple scattering
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January 2018 |
Learning approach to optical tomography
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January 2015 |
Optical diffraction tomography for high resolution live cell imaging
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January 2009 |
NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesis
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conference
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June 2021 |
Scalable Plug-and-Play ADMM With Convergence Guarantees
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January 2021 |
TU-FG-207A-04: Overview of the Low Dose CT Grand Challenge
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June 2016 |
A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction
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October 2017 |
Efficient and accurate inversion of multiple scattering with deep learning
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January 2018 |
Framing U-Net via Deep Convolutional Framelets: Application to Sparse-View CT
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June 2018 |
Plug-and-Play priors for model based reconstruction
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conference
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December 2013 |
The Little Engine That Could: Regularization by Denoising (RED)
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journal
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January 2017 |
Primal-Dual Plug-and-Play Image Restoration
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August 2017 |
A Plug-and-Play Priors Approach for Solving Nonlinear Imaging Inverse Problems
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journal
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December 2017 |
Zero-Shot Super-Resolution Using Deep Internal Learning
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conference
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June 2018 |
SIMBA: Scalable Inversion in Optical Tomography Using Deep Denoising Priors
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journal
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October 2020 |
Image Restoration Using Total Variation Regularized Deep Image Prior
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conference
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May 2019 |
RARE: Image Reconstruction Using Deep Priors Learned Without Groundtruth
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journal
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October 2020 |
Deep Image Prior
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journal
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March 2020 |
Scan‐specific robust artificial‐neural‐networks for k‐space interpolation (RAKI) reconstruction: Database‐free deep learning for fast imaging
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journal
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September 2018 |
“Double-DIP”: Unsupervised Image Decomposition via Coupled Deep-Image-Priors
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conference
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June 2019 |
Learning Implicit Fields for Generative Shape Modeling
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conference
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June 2019 |
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
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conference
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June 2019 |