FetalSleepNet achieves 86.6% accuracy in fetal sleep stage classification from ovine EEG by fine-tuning an adult model with spectral equalisation domain adaptation, outperforming baselines as the first such deep learning system.
Human fetal heart rate variability- characteristics of autonomic regulation in the third trimester of gesta- tion
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FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep Stage Classification
FetalSleepNet achieves 86.6% accuracy in fetal sleep stage classification from ovine EEG by fine-tuning an adult model with spectral equalisation domain adaptation, outperforming baselines as the first such deep learning system.