Cargando…
DDD TinyML: A TinyML-Based Driver Drowsiness Detection Model Using Deep Learning
Driver drowsiness is one of the main causes of traffic accidents today. In recent years, driver drowsiness detection has suffered from issues integrating deep learning (DL) with Internet-of-things (IoT) devices due to the limited resources of IoT devices, which pose a challenge to fulfilling DL mode...
Autores principales: | Alajlan, Norah N., Ibrahim, Dina M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10305041/ https://www.ncbi.nlm.nih.gov/pubmed/37420860 http://dx.doi.org/10.3390/s23125696 |
Ejemplares similares
-
TinyML
por: Warden, Pete
Publicado: (2019) -
TinyML: Enabling of Inference Deep Learning Models on Ultra-Low-Power IoT Edge Devices for AI Applications
por: Alajlan, Norah N., et al.
Publicado: (2022) -
A TinyML Deep Learning Approach for Indoor Tracking of Assets †
por: Avellaneda, Diego, et al.
Publicado: (2023) -
Smart Buildings: Water Leakage Detection Using TinyML
por: Atanane, Othmane, et al.
Publicado: (2023) -
Robustifying the Deployment of tinyML Models for Autonomous Mini-Vehicles
por: de Prado, Miguel, et al.
Publicado: (2021)