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Advanced Microsystems for Automotive Applications 2018

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Cover of 'Advanced Microsystems for Automotive Applications 2018'

Table of Contents

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    Book Overview
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    Chapter 1 All-Weather Vision for Automotive Safety: Which Spectral Band?
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    Chapter 2 Machine Learning Based Automatic Extrinsic Calibration of an Onboard Monocular Camera for Driving Assistance Applications on Smart Mobile Devices
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    Chapter 3 Towards Collaborative Perception for Automated Vehicles in Heterogeneous Traffic
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    Chapter 4 Real Time Recognition of Non-driving Related Tasks in the Context of Highly Automated Driving
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    Chapter 5 Affordable and Safe High Performance Vehicle Computers with Ultra-Fast On-Board Ethernet for Automated Driving
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    Chapter 6 The Disrupters: The First to Market Automation Technologies to Revolutionize Mobility
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    Chapter 7 TrustVehicle – Improved Trustworthiness and Weather-Independence of Conditionally Automated Vehicles in Mixed Traffic Scenarios
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    Chapter 8 Adaptation Layer Based Hybrid Communication Architecture: Practical Approach in ADAS&ME
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    Chapter 9 Assistance and Mitigation Strategies in Case of Impaired Motorcycle Riders: The ADAS&ME Case Study
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    Chapter 10 Towards a Privacy-Preserving Way of Vehicle Data Sharing – A Case for Blockchain Technology?
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    Chapter 11 Challenges and Opportunities of Artificial Intelligence for Automated Driving
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    Chapter 12 Light Electric Vehicle Design Tailored to Human Needs
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    Chapter 13 DCCS-ECU an Innovative Control and Energy Management Module for EV and HEV Applications
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    Chapter 14 Connectivity Design Considerations for a Dedicated Shared Mobility Vehicle
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    Chapter 15 Trends and Challenges of the New Mobility Society
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    Chapter 16 Roadmap for Accelerated Innovation in Level 4/5 Connected and Automated Driving
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6 tweeters


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Advanced Microsystems for Automotive Applications 2018
Published by
Springer International Publishing, November 2018
DOI 10.1007/978-3-319-99762-9
978-3-31-999761-2, 978-3-31-999762-9

Dubbert, Jörg, Müller, Beate, Meyer, Gereon

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 50%
Student > Bachelor 1 50%
Readers by discipline Count As %
Computer Science 1 50%
Engineering 1 50%