HSDDD: A Hybrid Scheme for the Detection of Distracted Driving through Fusion of Deep Learning and Handcrafted Features

Traditional methods for behavior detection of distracted drivers are not capable of capturing driver behavior features related to complex temporal features. With the goal to improve transportation safety and to reduce fatal accidents on roads, this research article presents a Hybrid Scheme for the D...

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Detalles Bibliográficos
Autores principales: Alkinani, Monagi H., Khan, Wazir Zada, Arshad, Quratulain, Raza, Mudassar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914727/
https://www.ncbi.nlm.nih.gov/pubmed/35271011
http://dx.doi.org/10.3390/s22051864

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914727/
https://www.ncbi.nlm.nih.gov/pubmed/35271011
http://dx.doi.org/10.3390/s22051864

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