A cross-domain framework for emotion and stress detection using WESAD, SCIENTISST-MOVE, and DREAMER datasets

Computer Science

• Deep Learning Method 100%
• Convolutional Neural Network 100%
• Transfer Learning 100%
• Affective Computing 100%
• Mental Disorder 100%
• Mental Health 100%
• Emotional State 50%
• Class Imbalance 50%
• Interpretability 50%
• Recognition System 50%
• Explainable Artificial Intelligence 50%
• Gradient-Weighted Class Activation Mapping 50%
• Monitoring Activity 50%
• Model Prediction 50%
• Generalizability 50%
• Feature Engineering 50%