Utilization of temporal autoencoder for semi-supervised intracranial eeg clustering and classification

HIGHLIGHTS

• who: Petr Nejedly from the Faculty Masaryk University, Rochester, MN, USA have published the paper: Utilization of temporal autoencoder for semi-supervised intracranial EEG clustering and classification, in the Journal: Scientific Reports Scientific Reports
• what: The aim of the autoencoder is to learn an input representation mapped in the low dimensional latent space. The authors introduced a semi-supervised method for iEEG clustering and classification.The main purpose of the method is to enable objective and fast inspection of novel big electrophysiological data (presurgical evaluation of iEEG or long-term data from neurostimulator with sensing . . .
  

   

  

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