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Deep Multimodal Emotion Recognition Techniques by wf wf is a document available to read on EtoBox.
This research article presents a novel deep multimodal emotion recognition system that utilizes electroencephalogram (EEG) and electrocardiogram (ECG) data to classify emotional states based on arousal and valence. The proposed architecture incorporates a modality-aware attention mechanism and a proxy-based multimodal loss function to enhance feature extraction and mitigate conflicts between different physiological signals. Experimental results demonstrate the effectiveness of this approach in improving emo
- Author
- wf wf
- Language
- EN