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Found 2 papers, 2 papers with code
Robust Source-Free Domain Adaptation for Fundus Image Segmentation
Unsupervised Domain Adaptation (UDA) is a learning technique that transfers knowledge learned in the source domain from labelled training data to the target domain with only unlabelled data.
XNet: Wavelet-Based Low and High Frequency Fusion Networks for Fully- and Semi-Supervised Semantic Segmentation of Biomedical Images
Perturbations in consistency-based semi-supervised models are often artificially designed.
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