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Real-time driver distraction recognition: A hybrid genetic deep network based approach
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Real-time driver distraction recognition: A hybrid genetic deep network based approach (2022)Real-time driver distraction recognition:…E2DR: A Deep Learning Ensemble-Based Driver Distraction Detection with Recommendations Model (2022)E2DR: A Deep Learning Ensembl…Driver distraction detection based on vehicle dynamics using naturalistic driving data (2022)Driver distraction detection …Automatic driver distraction detection using deep convolutional neural networks (2022)Automatic driver distraction …Driver Distraction Detection Methods: A Literature Review and Framework (2021)Driver Distraction Detection …Distracted Driver Detection Based on a CNN With Decreasing Filter Size (2021)Distracted Driver Detection B…Towards Computationally Efficient and Realtime Distracted Driver Detection With MobileVGG Network (2020)Towards Computationally Effic…HCF: A Hybrid CNN Framework for Behavior Detection of Distracted Drivers (2020)HCF: A Hybrid CNN Framework f…A Hybrid Deep Learning Approach for Driver Distraction Detection (2020)A Hybrid Deep Learning Approa…Driver Distraction Identification with an Ensemble of Convolutional Neural Networks (2019)Driver Distraction Identifica…Classification of Driver Distraction: A Comprehensive Analysis of Feature Generation, Machine Learning, and Input Measures (2019)Classification of Driver Dist…Can our phones keep us safe? A content analysis of smartphone applications to prevent mobile phone distracted driving (2018)Can our phones keep us safe? …Psychological Predictors of Problem Mobile Phone Use (2005)Three Approaches to Qualitative Content Analysis (2005)A model of the relationship between psychological characteristics, mobile phone addiction and use of mobile phones by Taiwanese university female students (2012)How do perceptions of risk and other psychological factors influence the use of in-vehicle information systems (IVIS)? (2019)Exploring drivers’ mental workload and visual demand while using an in-vehicle HMI for eco-safe driving (2020)Nomophobia: Is the Fear of Being without a Smartphone Associated with Problematic Use? (2020)Takeover Time in Highly Automated Vehicles: Noncritical Transitions to and From Manual Control (2017)Intelligent In‐Vehicle Interaction Technologies (2021)Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles (2022)Cell phone-induced failures of visual attention during simulated driving. (2003)Detecting Stress During Real-World Driving Tasks Using Physiological Sensors (2005)What's In A Name? 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References

  • 2019Driver Distraction Identification with an Ensemble of Convolutional Neural Networks307 cited
  • 2021Driver Distraction Detection Methods: A Literature Review and Framework189 cited
  • 2020HCF: A Hybrid CNN Framework for Behavior Detection of Distracted Drivers118 cited
  • 2020Towards Computationally Efficient and Realtime Distracted Driver Detection With MobileVGG Network103 cited
  • 2019Classification of Driver Distraction: A Comprehensive Analysis of Feature Generation, Machine Learning, and Input Measures96 cited
  • 2021Distracted Driver Detection Based on a CNN With Decreasing Filter Size96 cited
  • 2022Driver distraction detection based on vehicle dynamics using naturalistic driving data95 cited
  • 2022Automatic driver distraction detection using deep convolutional neural networks92 cited
  • 2020A Hybrid Deep Learning Approach for Driver Distraction Detection84 cited
  • 2018Can our phones keep us safe? A content analysis of smartphone applications to prevent mobile phone distracted driving75 cited
  • 2022E2DR: A Deep Learning Ensemble-Based Driver Distraction Detection with Recommendations Model58 cited

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