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

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...

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Bibliografiske detaljer
Institution som forfatter: SpringerLink (Online service)
Andre forfattere: Ghatee, Mehdi (Editor), Hashemi, S. Mehdi (Editor)
Format: Electronisk eBog
Sprog:engelsk
Udgivet: Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Udgivelse:1st ed. 2023.
Serier:Communications in Computer and Information Science, 1883
Fag:
Artificial intelligence.
Image processing > Digital techniques.
Computer vision.
Signal processing.
Computer networks .
Machine learning.
Artificial Intelligence.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Signal, Speech and Image Processing.
Computer Communication Networks.
Machine Learning.
Online adgang:https://doi.org/10.1007/978-3-031-43763-2
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Indholdsfortegnelse:
  • 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.

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