Scipediacontent: Scipediacontent moved page Draft Content 693977484 to Abouelnaga et al 2019a

2021-02-03T16:32:48Z

Scipediacontent moved page Draft Content 693977484 to Abouelnaga et al 2019a

Scipediacontent: Created page with " == Abstract == The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasin..."

2021-02-03T16:32:46Z

Created page with " == Abstract == The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasin..."

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== Abstract ==

The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasing over the last few years. Nearly fifth of these accidents are caused by distracted drivers. Existing work of distracted driver detection is concerned with a small set of distractions (mostly, cell phone usage). Unreliable ad-hoc methods are often used.In this paper, we present the first publicly available dataset for driver distraction identification with more distraction postures than existing alternatives. In addition, we propose a reliable deep learning-based solution that achieves a 90% accuracy. The system consists of a genetically-weighted ensemble of convolutional neural networks, we show that a weighted ensemble of classifiers using a genetic algorithm yields in a better classification confidence. We also study the effect of different visual elements in distraction detection by means of face and hand localizations, and skin segmentation. Finally, we present a thinned version of our ensemble that could achieve 84.64% classification accuracy and operate in a real-time environment.

Comment: arXiv admin note: substantial text overlap with arXiv:1706.09498

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_693977484-beopen5624-4413-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/1901.09097 http://arxiv.org/abs/1901.09097] under the license http://creativecommons.org/licenses/by/4.0/

* [http://dx.doi.org/10.1155/2019/4125865 http://dx.doi.org/10.1155/2019/4125865]

* [https://doi.org/10.1155/2019/4125865 https://doi.org/10.1155/2019/4125865] under the license http://creativecommons.org/licenses/by/4.0

* [http://downloads.hindawi.com/journals/jat/2019/4125865.pdf http://downloads.hindawi.com/journals/jat/2019/4125865.pdf],
: [http://downloads.hindawi.com/journals/jat/2019/4125865.xml http://downloads.hindawi.com/journals/jat/2019/4125865.xml],
: [http://dx.doi.org/10.1155/2019/4125865 http://dx.doi.org/10.1155/2019/4125865] under the license cc-by

* [http://dx.doi.org/10.1155/2019/4125865 http://dx.doi.org/10.1155/2019/4125865],
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/

* [https://dblp.uni-trier.de/db/journals/corr/corr1901.html#abs-1901-09097 https://dblp.uni-trier.de/db/journals/corr/corr1901.html#abs-1901-09097],
: [https://www.hindawi.com/journals/jat/2019/4125865 https://www.hindawi.com/journals/jat/2019/4125865],
: [http://downloads.hindawi.com/journals/jat/2019/4125865.pdf http://downloads.hindawi.com/journals/jat/2019/4125865.pdf],
: [https://academic.microsoft.com/#/detail/2912346386 https://academic.microsoft.com/#/detail/2912346386]

* [ ]

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Abouelnaga et al 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 693977484 to Abouelnaga et al 2019a

Scipediacontent: Created page with " == Abstract == The World Health Organization (WHO) reported 1.25 million deaths yearly due to road traffic accidents worldwide and the number has been continuously increasin..."