Self-DSNet: A Novel Self-ONNs Based Deep Learning Framework for Multimodal Driving Distraction Detection

Self-DSNet: A Novel Self-ONNs Based Deep Learning Framework for Multimodal Driving Distraction Detection

Distraction can cause delayed decision-making and slower awareness, posing significant risks in driving. For reliable driving systems, continuous monitoring of driver behavior is essential to mitigate the impact of distractions. Current strategies for distraction detection widely rely on machine lea...

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Bibliographic Details
Main Authors: Mamun Or Rashid, Md. Mosarrof Hossen, Mohammad Nashbat, Mazhar Hasan-Zia, Ali K. Ansaruddin Kunju, Amith Khandakar, Azad Ashraf, Molla Ehsanul Majid, Saad Bin Abul Kashem, Muhammad E. H. Chowdhury
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Driving distraction detection
self-organizing neural network (Self-ONN)
multimodal data
machine learning
driver behavior monitoring
vehicle dynamics
Online Access:https://ieeexplore.ieee.org/document/10902140/
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