mlsanityData to 14 Oct 2026

A XGBoost Algorithm-based Fatigue Recognition Model Using Face Detection

arXiv 2303.12727 ↗First posted 13 Mar 2023cs.CVcited by 0

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Abstract (arXiv)

As fatigue is normally revealed in the eyes and mouth of a person's face, this paper tried to construct a XGBoost Algorithm-Based fatigue recognition model using the two indicators, EAR (Eye Aspect Ratio) and MAR(Mouth Aspect Ratio). With an accuracy rate of 87.37% and sensitivity rate of 89.14%, the model was proved to be efficient and valid for further applications.

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