Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision-Reference-Cited by-同舟云学术

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Multivariate Approach to Alcohol Detection in Drivers by Sensors and Artificial Vision

Published:2019 Issue: Volume: Page:234-243
ISSN:0302-9743
Container-title:From Bioinspired Systems and Biomedical Applications to Machine Learning
language:
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Author:

Rosero-Montalvo Paul D.,López-Batista Vivian F.,Peluffo-Ordóñez Diego H.,Erazo-Chamorro Vanessa C.,Arciniega-Rocha Ricardo P.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-19651-6_23

Reference12 articles.

1. Assailly, J.-P.: Young people drunk-driving: process and outcome evaluation of preventive actions. In: von Holst, H., Nygren, Å., Andersson, Å.E. (eds.) Transportation, Traffic Safety and Health - Human Behavior, pp. 297–326. Springer, Heidelberg (2000). https://doi.org/10.1007/978-3-642-57266-1_18

2. Al-Youif, S., Ali, M.A.M., Mohammed, M.N.: Alcohol detection for car locking system. In: 2018 IEEE Symposium on Computer Applications and Industrial Electronics (ISCAIE), pp. 230–233. IEEE, April 2018. https://ieeexplore.ieee.org/document/8405475/

3. Paredes-Doig, A.L., del Rosario Sun-Kou, M., Comina, G.: Alcohols detection based on Pd-doped SnO $$<$$ inf $$>$$ 2 $$<$$ /inf $$>$$ sensors. In: 2014 IEEE 9th IberoAmerican Congress on Sensors, pp. 1–3. IEEE, October 2014. http://ieeexplore.ieee.org/document/6995514/

4. Drunk driving detection based on classification of multivariate time series. J. Saf. Res. 54, 61.e29–64 (2015)

5. Lecture Notes in Computational Vision and Biomechanics;V Nair,2019

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