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A Comprehensive Review of Machine Learning Advances on Data Change: A Cross-Field Perspective
In this review, we regroup domain shift and concept drift into a single research problem, namely the data change problem, with a systematic overview of state-of-the-art methods in the two research fields.
Improving Limited Supervised Foot Ulcer Segmentation Using Cross-Domain Augmentation
Existing segmentation models relying on extensive annotations are impractical in real-world scenarios with limited annotated data.
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