Cross-subject driver status detection from physiological signals based on hybrid feature selection and transfer learning-Reference-Cited by-同舟云学术

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Cross-subject driver status detection from physiological signals based on hybrid feature selection and transfer learning

Published:2019-12 Issue: Volume:137 Page:266-280
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Chen Lan-lan,Zhang Ao,Lou Xiao-guang

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference49 articles.

1. Ensemble feature selection for domain adaptation in speech emotion recognition;Abdelwahab,2017

2. Literature review on feature selection methods for high-dimensional data;Asir;International Journal of Computer Applications,2016

3. Fully automated real time fatigue detection of drivers through fuzzy expert systems;Azim,2014

4. Human factors in intelligent transportation systems;Barfield,2014

5. Hybrid computer vision system for drivers' eye recognition and fatigue monitoring;Bogusław;Neurocomputing,2014

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