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Recognizing blind spot check activity with car drivers based on decision tree classifiers [r-libre/265]

Kedowide, Colombiano; Gouin-Vallerand, Charles, & Vallières, Évelyne F. (2014). Recognizing blind spot check activity with car drivers based on decision tree classifiers. In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14). Québec, Canada.

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Content : Published Version
 
Item Type: Papers in Conference Proceedings
Refereed: Yes
Status: Published
Abstract: Blind spot check is important driving activity that is a good indicator of drivers’ proficiency and vigilance. By recognizing the blind spot check activity with drivers, it is possible to quantify and qualify the proficiency of the drivers, but also to cross validate this information with other data such the fatigue level. Thus, in this paper, we present a blind spot check activity recognition system where decision tree classifiers are modeled for each drivers and are used to automatically recognize the blind spot checks.
Official URL: http://www.aaai.org/ocs/index.php/WS/AAAIW14/paper...
Depositor: Gouin-Vallerand, Charles
Owner / Manager: Charles Gouin-Vallerand
Deposited: 23 Aug 2014 20:05
Last Modified: 16 Jul 2015 00:46

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