# A XGBoost Algorithm-based Fatigue Recognition Model Using Face Detection

arXiv: https://arxiv.org/abs/2303.12727 · HTML: https://mlsanity.com/paper/2303.12727/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 6 references that are in the map.
- First posted on arXiv 13 Mar 2023.

## 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.