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

<p dir="ltr">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 detecti...

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Bibliographic Details
Main Author: Mamun Or Rashid (21976373) (author)
Other Authors: Md. Mosarrof Hossen (21976376) (author), Mohammad Nashbat (17542194) (author), Mazhar Hasan-Zia (21399896) (author), Ali K. Ansaruddin Kunju (21323918) (author), Amith Khandakar (14151981) (author), Azad Ashraf (17541924) (author), Molla Ehsanul Majid (21976379) (author), Saad Bin Abul Kashem (19117156) (author), Muhammad E. H. Chowdhury (14150526) (author)
Published: 2025
Subjects:
Engineering
Automotive engineering
Biomedical engineering
Information and computing sciences
Artificial intelligence
Computer vision and multimedia computation
Data management and data science
Human-centred computing
Machine learning
Driving distraction detection
Self-organizing neural network (Self-ONN)
Multimodal data
Driver behavior monitoring
Vehicle dynamics
Vehicles
Feature extraction
Drives
Driver behavior
Biomedical monitoring
Data models
Brain modeling
Accidents
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