Deep learning models require vast amounts of data to produce accurate predictions, and this need becomes more acute every day as models grow in size and complexity. Even large datasets, such as the well-known ImageNet with more than a million images, are not sufficient to achieve state-of-the-art results in modern computer vision tasks. For this purpose, data augmentation techniques are…
]]>Medical image segmentation is a hot topic in the deep learning community. Proof of that is the number of challenges, competitions, and research projects being conducted in this area, which only rises year over year. Among all the different approaches to this problem, U-Net has become the backbone of many of the top-performing solutions for both 2D and 3D segmentation tasks. This is due to its…
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