Artificial Intelligence and Smart Vehicles

Local and Global Contextual Features Fusion for Pedestrian Intention Prediction.- Routes analysis and dependency detection based on traffic volume: a deep learning approach.- Road Sign Classification using Transfer Learning and Pre-Trained CNN Models.- Improving Safe Driving with Diabetic Retinopathy Detection.- A Bibliometric Analysis on Artificial Intelligence and Smart Vehicles.- Convolutional Neural Network and Long Short Term Memory on Inertial Measurement Unit sensors for Gait Phase Detection.- Real-time mobile mixed-character license plate recognition via deep learning convolutional neural network.- Evaluation of Drivers’ Hazard Perception in Simultaneous Longitudinal and Lateral Control of Vehicle Using a Driving Simulator.- Driver Identification by An Ensemble of CNNs Obtained from Majority-Voting Model Selection.- State-of-the-Art Analysis of the Performance of the Sensors Utilized in Autonomous Vehicles in Extreme Conditions.- Semantic Segmentation using Events and Combination of Events and Frames.- Deep learning-based concrete crack detection using YOLO architecture.- Generating Control Command for an Autonomous Vehicle Based on Environmental Information.- Fractal-Based Spatiotemporal Predictive Model for Car Crash Risk Assessment.