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Rethinking Superpixel Segmentation from Biologically Inspired Mechanisms
Recently, advancements in deep learning-based superpixel segmentation methods have brought about improvements in both the efficiency and the performance of segmentation.
USL-Net: Uncertainty Self-Learning Network for Unsupervised Skin Lesion Segmentation
Rather than risk potential pseudo-labeling errors or learning confusion by forcefully classifying these regions, we consider them as uncertainty regions, exempting them from pseudo-labeling and allowing the network to self-learn.
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