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Found 4 papers, 3 papers with code
Quantifying the Impact of Data Characteristics on the Transferability of Sleep Stage Scoring Models
First, when annotations on a target dataset are unavailable, which different data characteristics affect the sleep stage scoring performance the most and by how much?
TensorLayer: A Versatile Library for Efficient Deep Learning Development
Deep learning has enabled major advances in the fields of computer vision, natural language processing, and multimedia among many others.
DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
This demonstrated that, without changing the model architecture and the training algorithm, our model could automatically learn features for sleep stage scoring from different raw single-channel EEGs from different datasets without utilizing any hand-engineered features.
Ranked #4 on
Sleep Stage Detection
on MASS SS3
Mixed Neural Network Approach for Temporal Sleep Stage Classification
Use of this recording configuration with neural network deconvolution promises to make clinically indicated home sleep studies practical.
