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Battle of Algorithm: Machine Learning vs Deep Learning for Explainable Emotion Recognition from ECG Waveform
4th IEEE International Conference (IATMSI-2026)
The paper compares Machine Learning (ML) and Deep Learning (DL) methods to detect human emotions from EEG/ECG signals. It analyzes which approach gives better accuracy and better explainability when recognizing emotions from waveform data.
Goal: To find the best algorithm for accurate and interpretable emotion recognition.
Application: Used in areas like mental health monitoring, brain–computer interfaces, and affective computing.
Certificate Document