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Driving Behavior Classification Based on Oversampled Signals of Smartphone Embedded Sensors Using an Optimized Stacked-LSTM Neural Networks

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Telematics System in Usage Based Motor Insurance
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Behavioral Classification of Drivers for Driving Efficiency Related ADAS Using Artificial Neural Network
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Driver's style classification using jerk analysis
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An evaluation study of driver profiling fuzzy algorithms using smartphones
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Multi-source information fusion for drowsy driving detection based on wireless sensor networks
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Driving style recognition using fuzzy logic
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Aggressive Driving Detection Using Deep Learning-based Time Series Classification
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DrivingStyles: A smartphone application to assess driver behavior
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Driver behavior classification model based on an intelligent driving diagnosis system
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Online driving style recognition using fuzzy logic
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A Real-Time Multi-scale Vehicle Detection and Tracking Approach for Smartphones
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Energy Consumption Estimation in Electric Vehicles Considering Driving Style
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Need data for driver behaviour analysis? Presenting the public UAH-DriveSet
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Systematic literature review on driving behavior
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Driving behavior classification based on sensor data fusion using LSTM recurrent neural networks
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Examining the impact of driving style on the predictability and responsiveness of the driver: Real-world and simulator analysis
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Driver classification and driving style recognition using inertial sensors
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DriveSafe: An app for alerting inattentive drivers and scoring driving behaviors
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Driver Behavior Profiling Using Smartphones: A Low-Cost Platform for Driver Monitoring
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Driving style classification using long-term accelerometer information
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Driving Style Classification Using a Semisupervised Support Vector Machine
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Driving Style Recognition for Intelligent Vehicle Control and Advanced Driver Assistance: A Survey
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A Comprehensive Review of Driver Behavior Analysis Utilizing Smartphones
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CarSafe app
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An Overview on Study of Identification of Driver Behavior Characteristics for Automotive Control
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Rapid Driving Style Recognition in Car-Following Using Machine Learning and Vehicle Trajectory Data
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Crash-Prone Section Identification for Mountainous Highways Considering Multi-Risk Factors Coupling Effect
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Long Short-Term Memory
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A Review of Research on Driving Styles and Road Safety
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Driver behavior profiling: An investigation with different smartphone sensors and machine learning
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Wheels in the Head: Ridesharing as Monitored Performance
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A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms
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Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition
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Early Prediction of Driver's Action Using Deep Neural Networks
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AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)
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Adam: A Method for Stochastic Optimization
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Characterizing Driving Styles with Deep Learning

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