Self-supervised learning has emerged as a powerful paradigm to bridge the gap between data abundance and label scarcity in medical imaging. By constructing supervisory signals from the data ...
Self-supervised learning (SSL) has emerged as a powerful method for extracting meaningful representations from vast, unlabelled datasets, transforming computer vision and natural language processing.
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