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اللغة
العربية
العربية
March 3, 2026
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Deep learning for distracted driving recognition with multisource data: A comprehensive review
WH
Wenbin He
Zhengzhou University of Light Industry
SW
Shifeng Wang
Zhengzhou University of Light Industry
ZL
Zhaohui Liu
Yutong (China)
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Key Points
Distracted driving recognition using deep learning shows promising advances in safety technologies.
Key evidence indicates that multiple data sources enhance recognition accuracy in real-time applications.
The review examines recognition algorithms and their effectiveness across different datasets and scenarios.
Findings suggest that effective implementation may significantly reduce road accidents related to distractions.
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He et al. (Thu,) studied this question.
synapsesocial.com/papers/69a7676cbadf0bb9e87e0d78
https://doi.org/https://doi.org/10.1016/j.sysarc.2026.103730
Deep learning for distracted driving recognition with multisource data: A comprehensive review | Synapse