Towards Imbalanced Multiclass Driver Distraction Identification

Driver distraction is one of the leading causes of driving-related accidents worldwide. The ability to detect driver distraction preemptively is crucial to reducing the number of such accidents. This paper utilizes a novel multimodal dataset of thermal, visual, near-infrared, and physiological signa...

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Bibliographic Details
Main Authors: Kapotaksha Das, Mohamed Abouelenien, Mihai Burzo, Rada Mihalcea
Format: Article
Language:English
Published: LibraryPress@UF 2022-05-01
Series:Proceedings of the International Florida Artificial Intelligence Research Society Conference
Subjects:
Online Access:https://journals.flvc.org/FLAIRS/article/view/130710
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