M1m2: deep-learning-based real-time emotion recognition from neural activity

HIGHLIGHTS

• who: Sumya Akter and colleagues from the Department of Computer Science, Virginia Tech, Blacksburg, VA, USA have published the research: M1M2: Deep-Learning-Based Real-Time Emotion Recognition from Neural Activity, in the Journal: Sensors 2022, 22, x FOR PEER REVIEW of /2022/
• what: Research question 4 (RQ4): How much data and time is required for training the model to achieve a reasonable performance? Through this methodology, the CNN model of this paper demonstrated the best performance when compared to LSTM and Bidirectional LSTM. The authors propose a CNN model (M1) with residual connections, which . . .
  

   

  

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