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academic

Too many papers to update!

adain-style

Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization

alsb

Matlab Code for Image compressive sensing recovery using adaptively learned sparsifying basis via L0 minimization

bwgan

Code for the paper "Banach Wasserstein GAN"

cbdnet

Code for "Toward Convolutional Blind Denoising of Real Photographs", CVPR 2019

clang-parallel-ct

Parallel-beam CT (C/C++ ver.)

cnn-rpgd

Code for 'CNN-Based Projected Gradient Descent for Consistent Image'.

compsensing_dip

Compressed sensing with deep image prior algorithm

convolt

CONVOLT: CONVolutional Operator Learning Toolbox (for Matlab)

covid-19-ct-seg-benchmark

A Benchmark for Lung and Infection Segmentation in COVID-19 CT scans

ct-cycle_idnetity_gan_tensorflow

Cycle Consistent Adversarial Denoising Network for Multiphase Coronary CT Angiography

ct-denoising

ct-image-reconstruction

ct-red_cnn_tensorflow

Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network (RED-CNN)

ct-wgan_vgg_tensorflow

Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss

cyclegan-1

Tensorflow implementation of CycleGANs

d-amp_toolbox

This package contains the code to run Learned D-AMP, D-AMP, D-VAMP, D-prGAMP, and DnCNN algorithms. It also includes code to train Learned D-AMP, DnCNN, and Deep Image Prior U-net using the SURE loss.

dalimeeting.github.io

3rd-5th April, Lanzarote, Canary Islands

dcgan-tensorflow

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

decisiontree_python

A decision tree classifier implemented in python.

deep-image-prior

Image restoration with neural networks but without learning.

deep_energy

Deep-Energy: Unsupervised Training of Deep Neural Networks

domain-adaptation-mr

Deep Learning with Domain Adaptation for Accelerated Projection-Reconstruction MR

drgan-oct

drn

Dual Recursive Network for Fast Image Deraining (ICIP 2019)

dvh-prediction

Implemention of DVH prediction from the (contoured) anatomical scans ...

framing-u-net

Deep Convolutional Framelets: A General Deep Learning Framework for Inverse Problems

gan-hallucination

This projects investigates the possible hallucinations or adversarial attacks for solving linear inverse problems. The goal is to understand the possible hallucinations, define metrics to quantify the hallucination, and find regularization techniques to make deep reconstruction nets robust against hallucination.

get-r-cran-mirror-index

v1

gsr

Matlab code for Group-based Sparse Representation for Image Restoration