Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling

Research article (IEEE Transactions on Intelligent Transportation Systems, 2021) · cited 104× · AI/ML
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Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling

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Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling is a scholarly article[1].

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  • Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling. Retrieved May 24, 2026, from https://4ort.xyz/entity/intelligent-driver-drowsiness-detection-for-traffic-safety-based-on-multi-cnn-deep-model-and-facial-subsampling
MLA “Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/intelligent-driver-drowsiness-detection-for-traffic-safety-based-on-multi-cnn-deep-model-and-facial-subsampling.
BibTeX @misc{4ortxyz_intelligent-driver-drowsiness-detection-for-traffic-safety-based-on-multi-cnn-deep-model-and-facial-subsampling_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling}}, year = {2026}, url = {https://4ort.xyz/entity/intelligent-driver-drowsiness-detection-for-traffic-safety-based-on-multi-cnn-deep-model-and-facial-subsampling}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Intelligent Driver Drowsiness Detection for Traffic Safety Based on Multi CNN Deep Model and Facial Subsampling — https://4ort.xyz/entity/intelligent-driver-drowsiness-detection-for-traffic-safety-based-on-multi-cnn-deep-model-and-facial-subsampling (retrieved 2026-05-24)

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