no code implementations • 23 Jul 2018 • Karan Aggarwal, Swaraj Khadanga, Shafiq R. Joty, Louis Kazaglis, Jaideep Srivastava
We propose an end-to-end framework that uses a combination of deep convolution and recurrent neural networks to extract high-level features from raw flow signal with a structured output layer based on a conditional random field to model the temporal transition structure of the sleep stages.