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- W4362605391 abstract "Driver drowsiness detection methods have received significant research interest in recent years and have been used in a variety of contexts, including driver activity tracking and visual attention monitoring. Every year, drowsiness-related accidents result in serious injuries and fatalities. To address this serious global issue, researchers are developing new technologies to detect driver drowsiness. The objective of this article is to present a detailed review of driver drowsiness detection methods using various techniques. Some of the challenges faced while developing drowsiness detection systems are lack of consistency, fake alarms, and some related privacy concerns. Smart or intelligent cameras are being developed as a result of advances in computer vision technology to detect driver drowsiness and alert drivers to avoid accidents. Second, in addition to the level of accuracy achieved, a thorough investigation of the deep learning techniques is carried out." @default.
- W4362605391 created "2023-04-06" @default.
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- W4362605391 date "2023-03-02" @default.
- W4362605391 modified "2023-10-17" @default.
- W4362605391 title "Analysis of Driver Drowsiness Detection Methods" @default.
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- W4362605391 doi "https://doi.org/10.1109/icears56392.2023.10084986" @default.
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