UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation
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DOI: 10.1109/tmi.2019.2959609
Abstract: The state-of-the-art models for medical image segmentation are variants of U-Net and fully convolutional networks (FCN). Despite their success, these models have two limitations: (1) their optimal depth is apriori unknown, requiring extensive architecture search… read more here.
Keywords: image segmentation; unet redesigning; skip connections; segmentation ... See more keywords