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Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.
Efficient 3D U-Net model for volumetric semantic segmentation of medical images, built with PyTorch.
This is the source code for a PyTorch implementation of the U-Net model, which can be used to train custom models.
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