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A XGBoost Algorithm-based Fatigue Recognition Model Using Face Detection

Computer Vision and Pattern Recognition 2023-03-23 v1

Abstract

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.

Cite

@article{arxiv.2303.12727,
  title  = {A XGBoost Algorithm-based Fatigue Recognition Model Using Face Detection},
  author = {Xinrui Chen and Bingquan Zhang},
  journal= {arXiv preprint arXiv:2303.12727},
  year   = {2023}
}

Comments

6 pages;2 fiqures

R2 v1 2026-06-28T09:28:26.101Z