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This is a Quantitative Study study (also classified as: Experimental Study).

Dense-Attention CNN with Spatial-Attention Fusion for Robust Facial Expression Recognition

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Model improves accuracy in facial expression recognition, focusing on emotional regions with attention mechanisms.

A novel model improves accuracy by focusing on significant emotional regions in facial expressions, reducing variability.
The model achieved accuracy increases of 1.1% on CK+ and 2.7% on FER2013 datasets, demonstrating effectiveness.
This approach combines spatial attention with intra-class distance penalties to enhance network learning and performance.
The findings highlight the importance of attention in CNN models for recognizing nuanced emotional expressions effectively.

Li et al. (2025) studied this question.

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