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Artificial Intelligence and Smart Vehicles: First International Conference, ICAISV 2023, Tehran, Iran, May 24-25, 2023, Revised Selected Papers de Mehdi Ghatee

Artificial Intelligence and Smart Vehicles: First International Conference, ICAISV 2023, Tehran, Iran, May 24-25, 2023, Revised Selected Papers: Communications in Computer and Information Science, cartea 1883

Editat de Mehdi Ghatee, S. Mehdi Hashemi
en Limba Engleză Paperback – 5 oct 2023
This book constitutes the refereed proceedings of the First International Conference on Artificial Intelligence and Smart Vehicles, ICAISV 2023, held in Tehran, Iran, during May 24-25, 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
Ilustrații: XIV, 217 p. 118 illus., 108 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.33 kg
Ediția:1st ed. 2023
Editura: Springer Nature Switzerland
Colecția Springer
Seria Communications in Computer and Information Science

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.