An Effective Hybrid Model for EEG-Based Drowsiness Detection

dc.contributor.author	Budak, Umit
dc.contributor.author	Bajaj, Varun
dc.contributor.author	Akbulut, Yaman
dc.contributor.author	Atilla, Orhan
dc.contributor.author	Sengur, Abdulkadir
dc.date.accessioned	16/12/21 12:06
dc.date.available	16/12/21 12:06
dc.date.issued	2019
dc.identifier.issn	1530-437X
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/10079
dc.identifier.uri	https://doi.org/10.1109/JSEN.2019.2917850
dc.description.abstract	Early detection of driver drowsiness and the development of a functioning driver alertness system may support the prevention of numerous vehicular accidents worldwide. Wearable sensors and camera-based systems are generally employed in the driver drowsine
dc.language.iso	English
dc.publisher	Ieee-Inst Electrıcal Electronıcs Engıneers Inc
dc.source	Ieee Sensors Journal
dc.title	An Effective Hybrid Model for EEG-Based Drowsiness Detection
dc.type	Article
dc.identifier.issue	17
dc.identifier.startpage	7624
dc.identifier.endpage	7631
dc.identifier.doi	10.1109/JSEN.2019.2917850
dc.identifier.wos	WOS:000480379400053
dc.identifier.volume	19

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