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From Human Attention to Computational Attention

Overview of attention for book
Cover of 'From Human Attention to Computational Attention'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Why Do Computers Need Attention?
  3. Altmetric Badge
    Chapter 2 What Is Attention?
  4. Altmetric Badge
    Chapter 3 How to Measure Attention?
  5. Altmetric Badge
    Chapter 4 Where: Human Attention Networks and Their Dysfunctions After Brain Damage
  6. Altmetric Badge
    Chapter 5 Attention and Signal Detection: A Practical Guide
  7. Altmetric Badge
    Chapter 6 Effects of Attention in Visual Cortex: Linking Single Neuron Physiology to Visual Detection and Discrimination
  8. Altmetric Badge
    Chapter 7 Modeling Attention in Engineering
  9. Altmetric Badge
    Chapter 8 Bottom-Up Visual Attention for Still Images: A Global View
  10. Altmetric Badge
    Chapter 9 Bottom-Up Saliency Models for Still Images: A Practical Review
  11. Altmetric Badge
    Chapter 10 Bottom-Up Saliency Models for Videos: A Practical Review
  12. Altmetric Badge
    Chapter 11 Databases for Saliency Model Evaluation
  13. Altmetric Badge
    Chapter 12 Metrics for Saliency Model Validation
  14. Altmetric Badge
    Chapter 13 Study of Parameters Affecting Visual Saliency Assessment
  15. Altmetric Badge
    Chapter 14 Saliency Model Evaluation
  16. Altmetric Badge
    Chapter 15 Object-Based Attention: Cognitive and Computational Perspectives
  17. Altmetric Badge
    Chapter 16 Multimodal Saliency Models for Videos
  18. Altmetric Badge
    Chapter 17 Toward 3D Visual Saliency Modeling
  19. Altmetric Badge
    Chapter 18 Applications of Saliency Models
  20. Altmetric Badge
    Chapter 19 Attentive Content-Based Image Retrieval
  21. Altmetric Badge
    Chapter 20 Saliency and Attention for Video Quality Assessment
  22. Altmetric Badge
    Chapter 21 Attentive Robots
  23. Altmetric Badge
    Chapter 22 The Future of Attention Models: Information Seeking and Self-awareness
Attention for Chapter 16: Multimodal Saliency Models for Videos
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

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Citations

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Chapter title
Multimodal Saliency Models for Videos
Chapter number 16
Book title
From Human Attention to Computational Attention
Published in
Springer Series in Cognitive and Neural Systems, June 2016
DOI 10.1007/978-1-4939-3435-5_16
Book ISBNs
978-1-4939-3433-1, 978-1-4939-3435-5
Authors

Antoine Coutrot, Nathalie Guyader

Editors

Matei Mancas, Vincent P. Ferrera, Nicolas Riche, John G. Taylor

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Luxembourg 1 13%
Unknown 7 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Student > Bachelor 1 13%
Other 1 13%
Researcher 1 13%
Professor > Associate Professor 1 13%
Other 0 0%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 2 25%
Philosophy 1 13%
Psychology 1 13%
Medicine and Dentistry 1 13%
Engineering 1 13%
Other 0 0%
Unknown 2 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 July 2016.
All research outputs
#14,771,495
of 25,992,468 outputs
Outputs from Springer Series in Cognitive and Neural Systems
#1
of 1 outputs
Outputs of similar age
#190,567
of 368,997 outputs
Outputs of similar age from Springer Series in Cognitive and Neural Systems
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 2.8. This one scored the same or higher as 0 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 368,997 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them