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Driver distraction detection using semi-supervised lightweight vision transformer
12 references·0 citing·36 second hop
Driver distraction detection using semi-supervised lightweight vision transformer (2023)Driver distraction detection using semi-s…Vision-Language Models Can Identify Distracted Driver Behavior From Naturalistic Videos (2024)Vision-Language Models Can Id…Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open challenges (2014–2021) (2022)Detecting and recognizing dri…A review of driver fatigue detection and its advances on the use of RGB-D camera and deep learning (2022)A review of driver fatigue de…Driver behavior detection via adaptive spatial attention mechanism (2021)Driver behavior detection via…A survey on vision-based driver distraction analysis (2021)A survey on vision-based driv…A Survey on Driver Behavior Analysis From In-Vehicle Cameras (2021)A Survey on Driver Behavior A…HCF: A Hybrid CNN Framework for Behavior Detection of Distracted Drivers (2020)HCF: A Hybrid CNN Framework f…A novel public dataset for multimodal multiview and multispectral driver distraction analysis: 3MDAD (2020)A novel public dataset for mu…A Comprehensive Review of Driver Behavior Analysis Utilizing Smartphones (2019)A Comprehensive Review of Dri…Detection of Distracted Driver Using Convolutional Neural Network (2018)Detection of Distracted Drive…Real-time Distracted Driver Posture Classification (2017)Real-time Distracted Driver P…Recent Trends in Driver Safety Monitoring Systems: State of the Art and Challenges (2016)Recent Trends in Driver Safet…NHTSA DRIVER DISTRACTION RESEARCH: PAST, PRESENT, AND FUTURE (2001)Driver distraction and driver inattention: Definition, relationship and taxonomy (2011)Driver Inattention Monitoring System for Intelligent Vehicles: A Review (2011)A data analytic framework for physical fatigue management using wearable sensors (2020)Driver Fatigue Detection Based on Convolutional Neural Networks Using EM-CNN (2020)Driver fatigue transition prediction in highly automated driving using physiological features (2020)Takeover Time in Highly Automated Vehicles: Noncritical Transitions to and From Manual Control (2017)Real‐time detection of distracted driving based on deep learning (2018)Handbook of Human Factors and Ergonomics Methods (2004)Detecting Driver Drowsiness Based on Sensors: A Review (2012)Human mobility: Models and applications (2018)Early Identification and Detection of Driver Drowsiness by Hybrid Machine Learning (2021)Survey and Synthesis of State of the Art in Driver Monitoring (2021)Comprehensive study of driver behavior monitoring systems using computer vision and machine learning techniques (2024)A Survey on State-of-the-Art Drowsiness Detection Techniques (2019)Driver Activity Recognition for Intelligent Vehicles: A Deep Learning Approach (2019)Driver behavior detection and classification using deep convolutional neural networks (2020)Distracted Driver Detection Based on a CNN With Decreasing Filter Size (2021)YawDD (2014)Driver Distraction Identification with an Ensemble of Convolutional Neural Networks (2019)AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perception (2023)Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance (2002)Advancements in the Intelligent Detection of Driver Fatigue and Distraction: A Comprehensive Review (2024)Driver Behavior Analysis for Safe Driving: A Survey (2015)Driver Drowsiness Detection via a Hierarchical Temporal Deep Belief Network (2017)Driver distraction: The effects of concurrent in-vehicle tasks, road environment complexity and age on driving performance (2005)Effects of visual and cognitive load in real and simulated motorway driving (2005)Quantitative Identification of Driver Distraction: A Weakly Supervised Contrastive Learning Approach (2023)CBAM VGG16: An efficient driver distraction classification using CBAM embedded VGG16 architecture (2024)Technologies for detecting and monitoring drivers' states: A systematic review (2024)A critical review of the psychophysiology of driver fatigue (2001)Real-Time System for Monitoring Driver Vigilance (2006)A multi-modal driver emotion dataset and study: Including facial expressions and synchronized physiological signals (2023)Fatigue at the wheel: A non-visual approach to truck driver fatigue detection by multi-feature fusion (2024)A Multi-Modality Attention Network for Driver Fatigue Detection Based on Frontal EEG, EDA and PPG Signals (2025)Towards Computationally Efficient and Realtime Distracted Driver Detection With MobileVGG Network (2020)
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References

  • 2017Real-time Distracted Driver Posture Classification193 cited
  • 2018Detection of Distracted Driver Using Convolutional Neural Network184 cited
  • 2016Recent Trends in Driver Safety Monitoring Systems: State of the Art and Challenges168 cited
  • 2020HCF: A Hybrid CNN Framework for Behavior Detection of Distracted Drivers118 cited
  • 2019A Comprehensive Review of Driver Behavior Analysis Utilizing Smartphones115 cited
  • 2021A Survey on Driver Behavior Analysis From In-Vehicle Cameras107 cited
  • 2020A novel public dataset for multimodal multiview and multispectral driver distraction analysis: 3MDAD77 cited
  • 2022A review of driver fatigue detection and its advances on the use of RGB-D camera and deep learning72 cited
  • 2021A survey on vision-based driver distraction analysis70 cited
  • 2022Detecting and recognizing driver distraction through various data modality using machine learning: A review, recent advances, simplified framework and open challenges (2014–2021)70 cited
  • 2024Vision-Language Models Can Identify Distracted Driver Behavior From Naturalistic Videos68 cited
  • 2021Driver behavior detection via adaptive spatial attention mechanism56 cited

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