Trick to remember UNET architecture | Image segementation

U-NET is a convolutional neural network architecture that was developed for biomedical image segmentation by Olaf Ronneberger in the year 2015, at the University of Freiburg, Germany. It is one of the most popularly used architectures for any segmentation task. It is a fully convolutional neural network that is designed to learn from fewer training samples.
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