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Unstable appearance variations can lead to unreliable pseudo labels, but SAUF-Net's innovative structure-aware approach dramatically enhances segmentation accuracy in low-label settings.
KENDO achieves up to 5x faster Bayesian optimization and 27x faster active learning while enhancing predictive performance.
