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My model zoo

A list of all the neural networks I have implemented. All of them are written in TensorFlow 2.x style. Some of them are using the functional API, some others (the most recent ones as I find it way more convenient) are using the subclassing API.

The standalone tick indicates whether all the model can be found in one file, and only has TensorFlow imports.

Model Name Paper Original Implementation My Implementation Task Standalone
FocNet FOCNet: A Fractional Optimal Control Network for Image Denoising Matlab, MatConvNet tf-focnet Image denoising ✔️
MWCNN Multi-level Wavelet-CNN for Image Restoration Matlab, MatConvNet tf-mwcnn Image denoising, SISR ✔️
DIDN Deep Iterative Down-Up CNN for Image Denoising Python, Pytorch tf-didn Image denoising ✔️
ELDRN Exponential linear unit dilated residual network for digital image denoising ❌ tf-eldrn Image denoising ✔️
U-net U-Net: Convolutional Networks for Biomedical Image Segmentation Matlab, Caffe tf-unet Any kind of image-to-image problem Originally image segmentation ✔️
TDV Total Deep Variation for Linear Inverse Problems Python, Pytorch tf-tdv Inverse Problems ✔️
KIKI-net KIKI-net: Cross-Domain Convolutional Neural Networks for Reconstructing Undersampled Magnetic Resonance Images ❌ fastmri-reproducible-benchmark MR Image reconstruction ❌
Cascade-net A Deep Cascade of Convolutional Neural Networks for Dynamic MR Image Reconstruction Python, Pytorch fastmri-reproducible-benchmark MR Image reconstruction ❌
PD-net Learned Primal-dual Reconstruction Python, TensorFlow 1.x fastmri-reproducible-benchmark MR Image reconstruction Originally CT reconstruction ❌
XPDNet XPDNet for MRI Reconstruction: an Application to the fastMRI 2020 Brain Challenge ❌ fastmri-reproducible-benchmark MR Image reconstruction ❌

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A list of all the neural networks I have implemented

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deep-learning model-zoo tensorflow neural-networks

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