Learning spatiotemporal graph representations for visual perception using eeg signals

HIGHLIGHTS

• who: -Visual perception and collaborators from the where , and , are the weights that regulate the influence of all electrodes and are learned by the networkG() indicates the activation function, after performing grid search (between ELU, ReLU, and sigmoid function) have published the paper: Learning Spatiotemporal Graph Representations for Visual Perception using EEG Signals, in the Journal: (JOURNAL)
• what: The authors aimed to classify single-trial electroencephalography signals evoked by stimuli into their corresponding semantic category. The above mention studies focused on feature extraction while modeling connections between electrodes but failed to extract channel-wise features . . .
  

   

  

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