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Traffic Mining Applied to Police Activities

Overview of attention for book
Cover of 'Traffic Mining Applied to Police Activities'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Data and Analytics Framework. How Public Sector Can Profit from Its Immense Asset, Data
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    Chapter 2 Advancements in Mobility Data Analysis
  4. Altmetric Badge
    Chapter 3 Towards a Pervasive and Predictive Traffic Police
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    Chapter 4 A Process Mining Approach to the Identification of Normal and Suspect Traffic Behavior
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    Chapter 5 Detecting Criminal Behaviour Patterns in Spain and Italy Using Formal Concept Analysis
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    Chapter 6 Efficient and Accurate Traffic Flow Prediction via Fast Dynamic Tensor Completion
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    Chapter 7 Reducing the Risk of Accidents with Not Insured British Vehicles in Southern Spain
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    Chapter 8 Unsupervised Classification of Routes and Plates from the Trap-2017 Dataset
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    Chapter 9 Vehicle Classification Based on Convolutional Networks Applied to FMCW Radar Signals
  11. Altmetric Badge
    Chapter 10 Traffic Data: Exploratory Data Analysis with Apache Accumulo
  12. Altmetric Badge
    Chapter 11 Exploiting Recurrent Neural Networks for Gate Traffic Prediction
Attention for Chapter 8: Unsupervised Classification of Routes and Plates from the Trap-2017 Dataset
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4 Mendeley
Summary
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Chapter title
Unsupervised Classification of Routes and Plates from the Trap-2017 Dataset
Chapter number 8
Book title
Traffic Mining Applied to Police Activities
Published by
Springer, Cham, October 2017
DOI 10.1007/978-3-319-75608-0_8
Book ISBNs
978-3-31-975607-3, 978-3-31-975608-0
Authors

Massimo Bernaschi, Alessandro Celestini, Stefano Guarino, Flavio Lombardi, Enrico Mastrostefano, Bernaschi, Massimo, Celestini, Alessandro, Guarino, Stefano, Lombardi, Flavio, Mastrostefano, Enrico

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 25%
Student > Bachelor 1 25%
Researcher 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Unspecified 1 25%
Unknown 1 25%

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