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This document presents a lightweight facial expression detection model designed for monitoring depression in the elderly, addressing the need for continuous emotional monitoring in low-resource settings. The proposed system improves detection accuracy by integrating advanced computer vision techniques while maintaining compatibility with edge devices, achieving a mean average precision of 91.5% and a frame rate of 26 FPS. Experimental results demonstrate its effectiveness in real-world applications, highlig

Author

Paulo

Language

EN