U-Net is a deep learning architecture used for semantic segmentation tasks in image analysis. It was introduced by Olaf Ronneberger, Philipp Fischer, and Thomas Brox in a paper titled “U-Net…

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U-Net is a deep learning architecture used for semantic segmentation tasks in image analysis. It was introduced by Olaf Ronneberger, Philipp Fischer, and Thomas Brox in a paper titled ‘U-Net: Convolutional Networks for Biomedical Image Segmentation’ It is particularly effective for biomedical image segmentation.

Cook your First U-Net in PyTorch