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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: arxiv.org/abs/1505.04597
The code from this video is available at: github.com/bnsreenu/python_fo...