Artificial Intelligence and Smart Vehicles
Editat de Mehdi Ghatee, S. Mehdi Hashemien Limba Engleză Paperback – 5 oct 2023
The 14 full papers included in this book were carefully reviewed and selected from 93 submissions. They were organized in topical sections as follows: machine learning, data mining, machine vision, image processing, signal analysis, decision support systems, expert systems, and their applications in smart vehicles.
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Specificații
ISBN-13: 9783031437625
ISBN-10: 3031437624
Pagini: 232
Ilustrații: XIV, 217 p. 118 illus., 108 illus. in color.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.36 kg
Ediția:1st edition 2023
Editura: Springer
Locul publicării:Cham, Switzerland
ISBN-10: 3031437624
Pagini: 232
Ilustrații: XIV, 217 p. 118 illus., 108 illus. in color.
Dimensiuni: 155 x 235 x 13 mm
Greutate: 0.36 kg
Ediția:1st edition 2023
Editura: Springer
Locul publicării:Cham, Switzerland
Cuprins
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.