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Shandong Women鈥檚 University
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Teachability in representation learning boosts 2D-3D matching robustness, achieving state-of-the-art results even in challenging conditions.
SwinSleepNet outperforms traditional models by effectively capturing both intra-epoch microstructures and inter-epoch dependencies, leading to significant improvements in sleep stage classification accuracy.
LGFNet achieves significant accuracy improvements in sleep staging, particularly in challenging transition segments, outperforming existing methods by notable margins.
