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Unified Evaluation Benchmark Proposed for ECG-Based Emotion Recognition Models
A new arXiv paper argues that deep learning research on automated emotion recognition from electrocardiogram signals is hard to compare because studies differ in preprocessing, training and evaluation setups. The authors present a unified evaluation framework intended to allow fairer, more direct comparison between architectures. The work is a cross-listing on arXiv's machine learning section.