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MDT-Net: Multi-domain Transfer by Perceptual Supervision for Unpaired Images in OCT Scan
Furthermore, we take the transfer results as additional training data for fluid segmentation to prove the advantage of our model indirectly, i. e., in the task of data adaptation and augmentation.
Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts
In this paper, we introduce \emph{extreme consistency}, which overcomes the above limitations, by maximally leveraging unlabeled data from the same or a different domain in a teacher-student semi-supervised paradigm.
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