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Segmentation architectures in computer vision refer to the design principles and specific network structures used to
Early approaches to segmentation often involved post-processing steps applied to classification networks. However, the development of
Encoder-decoder architectures are a common paradigm. The encoder part, typically a standard convolutional network, progressively downsamples
More advanced architectures like U-Net, DeepLab, and Mask R-CNN build upon these fundamental concepts. U-Net, for