Virtual and augmented reality for automobile industry : innovation vision and applications / Aboul Ella Hassanien, Deepak Gupta, Ashish Khanna, Adam Slowik, editors.
2022
TL240
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Details
Title
Virtual and augmented reality for automobile industry : innovation vision and applications / Aboul Ella Hassanien, Deepak Gupta, Ashish Khanna, Adam Slowik, editors.
ISBN
9783030941024 (electronic bk.)
3030941027 (electronic bk.)
9783030941017
3030941019
3030941027 (electronic bk.)
9783030941017
3030941019
Published
Cham, Switzerland : Springer, 2022.
Language
English
Description
1 online resource (1 volume) : illustrations (black and white, and color).
Item Number
10.1007/978-3-030-94102-4 doi
Call Number
TL240
Dewey Decimal Classification
629.2028568
Summary
This book presents the augmented reality (AR) and virtual reality (VR) automotive applications. It unites automobile with a leading technology i.e. augmented and virtual reality and uses the advantages of the latter to solve the problems faced by the former. The book highlights the reasons for the growing abundance and complexity in this sector. Virtual and augmented reality presents a powerful engineering tool that finds application in various engineering fields. It brings new possibilities that result is increasing of productivity and reliability of production, quality of products and processes. The book further illustrates the possible challenges in its applications and suggests ways to overcome them. The book includes nine chapters focusing on automobile collision avoidance, self-driving cars, autonomous vehicles, navigation systems, and many more applications.
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Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Series
Studies in systems, decision and control ; v. 412.
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Table of Contents
Automotive Collision Avoidance System: A Review
Autonomous vehicle assisted by heads up display (HUD) with augmented reality based on Machine learning techniques
Optimal Stacked Sparse Autoencoder based Traffic Flow Prediction in Intelligent Transportation Systems
Hand Gesture Recognition for Real-Time Game Play using Background Elimination and Deep Convolution Neural Network.
Autonomous vehicle assisted by heads up display (HUD) with augmented reality based on Machine learning techniques
Optimal Stacked Sparse Autoencoder based Traffic Flow Prediction in Intelligent Transportation Systems
Hand Gesture Recognition for Real-Time Game Play using Background Elimination and Deep Convolution Neural Network.