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PyTorch Implementation of Paper "U-Net: Convolutional Networks for Biomedical Image Segmentation"

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U-Net: PyTorch Implementation for Biomedical Image Segmentation

This repository provides a PyTorch implementation of the U-Net, a convolutional neural network architecture for biomedical image segmentation. The U-Net has been widely used in various medical image analysis tasks.

Key Features

  • Implementation of the U-Net architecture in PyTorch
  • Training and evaluation scripts for biomedical image segmentation tasks

Paper

The implementation is based on the paper "U-Net: Convolutional Networks for Biomedical Image Segmentation" by Olaf Ronneberger, Philipp Fischer, and Thomas Brox.

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PyTorch Implementation of Paper "U-Net: Convolutional Networks for Biomedical Image Segmentation"

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