Many deep learning architectures have been proposed to solve various image processing challenges. SOme of the well known architectures include LeNet, ALexNet, VGG, and Inception. U-net is a relatively new architecture proposed by Ronneberger et al. for semantic image segmentation. This video explains the U-Net architecture; a good understanding is essential before coding.

Link to the original U-Net paper: [ Ссылка ]

The code from this video is available at: [ Ссылка ]

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