Synthetic distracted driving (SynDD1) dataset for analyzing distracted behaviors and various gaze zones of a driver

This article presents a synthetic distracted driving (SynDD1) dataset for machine learning models to detect and analyze drivers' various distracted behavior and different gaze zones. We collected the data in a stationary vehicle using three in-vehicle cameras positioned at locations: on the das...

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Detalles Bibliográficos
Autores principales: Rahman, Mohammed Shaiqur, Venkatachalapathy, Archana, Sharma, Anuj, Wang, Jiyang, Gursoy, Senem Velipasalar, Anastasiu, David, Wang, Shuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9730022/
https://www.ncbi.nlm.nih.gov/pubmed/36506800
http://dx.doi.org/10.1016/j.dib.2022.108793

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9730022/
https://www.ncbi.nlm.nih.gov/pubmed/36506800
http://dx.doi.org/10.1016/j.dib.2022.108793

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