Helper Module for Deep Learning.
API documentation of pynet.modelsΒΆ
Module that provides common networks.
| pynet.models.resnet |
The Residual Auto-Endocer network (ResAENet). |
| pynet.models.brainnetcnn |
BrainNetCNNs are convolutional neural networks for connectomes. |
| pynet.models.torchvisnet |
Import classifier models defined in torchvision. |
| pynet.models.deeplabnet |
The Deep Labeling Network for Semantic Image Segmentation. |
| pynet.models.voxelmorphnet |
Unsupervised Learning with CNNs for Image Registration |
| pynet.models.cam |
Module that provides reorganized networks to perform class activation map. Networks must have features/classifier methods for the convolutional part of the network, and the fully connected part. |
| pynet.models.vtnet |
Volume Tweening Network (VTN) and Affine and Dense Deformable Network (ADDNet) for Unsupervised medical Image Registration. |
| pynet.models.unet |
The U-Net is a convolutional encoder-decoder neural network. |
| pynet.models.rcnet |
Recursive Cascaded Networks (RCNet) for Unsupervised Medical Image Registration using and Dense Deformable Network (ADDNet) and Volume Tweening Network (VTN). |
| pynet.models.nvnet |
NvNet: combination of Vnet and VAE (variation auto-encoder). |
| pynet.models.deepcluster |
Deep Clustering for Unsupervised Learning of Visual Features. |
| pynet.models.sononet |
Sononet is a CNN architecture with two components: a feature extractor module and an adaptation module. |
| pynet.models.pspnet |
The Pyramid Scene Parsing Network. |
| pynet.models.braingengan |
3D MRI Brain Generation with Generative Adversarial Networks (BGGAN) with Variational Auto Encoder (VAE). |
| pynet.models.attention |
The Spatiotemporal Attention Autoencoder network (STAAENet). |
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