GateSleepNet: A Dual-Level Spatiotemporal Graph-Transformer Architecture for Automatic Sleep Staging
Abstract: Automatic sleep staging is critical for understanding sleep patterns and diagnosing sleep-related disorders, yet traditional manual scoring methods remain time-consuming, labor-intensive, ...
The rapid development in pseudo-labeling and consistency regularization has significantly advanced semi-supervised learning in computer vision. However, these methods have notable limitations.
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