Optimization of deep architectures for eeg signal classification: an automl approach using evolutionary algorithms

HIGHLIGHTS

• who: Diego Aquino-Brítez and collaborators from the Department of Computer Architecture and Technology, University of Granada, Granada, Spain have published the research work: Optimization of Deep Architectures for EEG Signal Classification: An AutoML Approach Using Evolutionary Algorithms, in the Journal: Sensors 2021, 21, 2096. of /2021/
• what: The authors propose a method for optimizing Deep Learning models not only the hyperparameters but also their structure which is able to propose solutions that consist of different architectures due to different layer combinations. The authors demonstrate that optimized architectures improve the energy efficiency with respect . . .
  

   

  

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