Comparison of eye and face features on drowsiness analysis

HIGHLIGHTS

• who: I-Hsi Kao and Ching-Yao Chan from the California Partners for Advanced Transportation Technology, University of California, Berkeley, CA, USA have published the paper: Comparison of Eye and Face Features on Drowsiness Analysis, in the Journal: Sensors 2022, 22, x FOR PEER REVIEW of /2022/
• what: This work analyzes the attentions of individual neurons in the learning model to understand how neural networks interpret drowsiness. This work proposed a feature analysis method K-nearest neighbors Sigma (KNN-Sigma) to estimate the homogeneous concentration and heterogeneous separation of the extracted features. In , an ensemble . . .
  

   

  

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