A multi-branch convolutional neural network with squeeze-and-excitation attention blocks for eeg-based motor imagery signals classification

HIGHLIGHTS

• who: Ghadir Ali Altuwaijri and colleagues from the Department of Computer Engineering, College of Computer and Information Sciences (CCIS), Centre of Smart Robotics Research (CS R), King Saud University, Riyadh, Saudi Arabia have published the Article: A Multi-Branch Convolutional Neural Network with Squeeze-and-Excitation Attention Blocks for EEG-Based Motor Imagery Signals Classification, in the Journal: Diagnostics 2022, 12, x FOR PEER REVIEW of /2022/
• what: The aim of this research is to develop an endto-end classification model based on deep learning that is capable of reliably categorizing MI-EEG-based signals . . .
  

   

  

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