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optimisticbear/matlabsadn

By optimisticbear

•Updated about 6 years ago

MatlabR2016b for SADN computing

Image
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optimisticbear/matlabsadn repository overview

⁠The Image For SADN

MatlabR2016b is installed in this image to run the SADN code.

⁠SADN code comes from : https://github.com/yqx7150/SADN⁠

⁠The details are as follows:
⁠SADN (Synthesis-analysis deconvolutional network for compressed sensing)

%% The Code is created based on the method described in the following papers:
% Q. Liu, H. Leung, "Synthesis-analysis deconvolutional network for compressed sensing," Image Processing (ICIP), 2017 IEEE International Conference on. IEEE, 2017: 1940-1944.
% Author: Q. Liu, H. Leung
% Date : 09/2018
% Version : 1.0
% The code and the algorithm are for non-comercial use only.
% Copyright 2018, Department of Electronic Information Engineering, Nanchang University.
% SADN - Synthesis-analysis deconvolutional network

  • Predual dictionary learning (PDL) / augmented Lagrangian multi-scale dictionary learning(ALM-DL) [Paper]⁠ [Code]⁠

  • Adaptive dictionary learning in sparse gradient domain for image recovery [Paper]⁠ [Code]⁠

  • Highly undersampled magnetic resonance image reconstruction using two-level Bregman method with dictionary updating [Paper]⁠ [Code]⁠

  • Convolutional Sparse Coding in Gradient Domain for MRI Reconstruction [Paper]⁠ [Code]⁠

  • Field-of-Experts Filters Guided Tensor Completion [Paper]⁠ [Code]⁠ [Slide]⁠

  • Sparse and dense hybrid representation via subspace modeling for dynamic MRI [Paper]⁠ [Code]⁠

  • IFR-Net: Iterative Feature Refinement Network for Compressed Sensing MRI [Paper]⁠ [Code]⁠

  • A Comparative Study of CNN-based Super-resolution Methods in MRI Reconstruction and Its Beyond [Paper]⁠ [Code]⁠


⁠How to use this image

⁠Start
docker run -it [Image ID] /bin/bash
⁠Run the SADN code
cd /home/Matlab/SADN-master
matlab -nodesktop -nosplash -r SADN_realvalue_demo

Tag summary

Content type

Image

Digest

Size

15.3 GB

Last updated

about 6 years ago

docker pull optimisticbear/matlabsadn:1.0