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Computation and Big Data for Transport

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Cover of 'Computation and Big Data for Transport'

Table of Contents

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    Book Overview
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    Chapter 1 Digital Technologies for Transport and Mobility: Challenges, Trends and Perspectives
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    Chapter 2 Cyber Security in Aviation, Maritime and Automotive
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    Chapter 3 Operation of Transport and Logistics in a Time of (Cyber)Insecurity
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    Chapter 4 New Data and Methods for Modelling Future Urban Travel Demand: A State of the Art Review
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    Chapter 5 Maritime Transport and the Threat of Bio Invasion and the Spread of Infectious Disease
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    Chapter 6 Application of a Knowledge Discovery Process to Study Instances of Capacitated Vehicle Routing Problems
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    Chapter 7 A New Multi-objective Solution Approach Using ModeFRONTIER and OpenTrack for Energy-Efficient Train Timetabling Problem
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    Chapter 8 Development of New Lagrangian Computational Methods for Ice-Ship Interaction Problems: NICESHIP Project
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    Chapter 9 Delivery Service in Congested Urban Areas
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    Chapter 10 Current CAE Trends in the Automotive Industry
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    Chapter 11 Establishment of MoS in Chile: Pertinence Assessment Through an Analysis of Previous Scenarios
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    Chapter 12 Radars in Transport Applications
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    Chapter 13 Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks
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    Chapter 14 Distortions in Large Aluminum Forgings: Current Situation and Simulation Challenges
Attention for Chapter 13: Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks
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Citations

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Chapter title
Using Aerial Platforms in Predicting Water Quality Parameters from Hyperspectral Imaging Data with Deep Neural Networks
Chapter number 13
Book title
Computation and Big Data for Transport
Published by
Springer, Cham, February 2020
DOI 10.1007/978-3-030-37752-6_13
Book ISBNs
978-3-03-037751-9, 978-3-03-037752-6
Authors

Taina Hakala, Ilkka Pölönen, Eija Honkavaara, Roope Näsi, Teemu Hakala, Antti Lindfors, Hakala, Taina, Pölönen, Ilkka, Honkavaara, Eija, Näsi, Roope, Hakala, Teemu, Lindfors, Antti

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 33%
Student > Doctoral Student 1 33%
Unknown 1 33%
Readers by discipline Count As %
Computer Science 2 67%
Social Sciences 1 33%