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A Review of Hidden Markov Models and Recurrent Neural Networks for Event Detection and Localization in Biomedical Signals
How to develop a model that can describe the transition between processes in time?
Upper Esophageal Sphincter Opening Segmentation with Convolutional Recurrent Neural Networks in High Resolution Cervical Auscultation
Upper esophageal sphincter is an important anatomical landmark of the swallowing process commonly observed through the kinematic analysis of radiographic examinations that are vulnerable to subjectivity and clinical feasibility issues.
Single neuron-based neural networks are as efficient as dense deep neural networks in binary and multi-class recognition problems
Recent advances in neuroscience have revealed many principles about neural processing.
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