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Computer Vision – ECCV 2020 Workshops

Overview of attention for book
Computer Vision – ECCV 2020 Workshops
Springer International Publishing

Table of Contents

  1. Altmetric Badge
    Book Overview
Attention for Chapter: Evaluating Input Perturbation Methods for Interpreting CNNs and Saliency Map Comparison
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (68th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

policy
1 policy source
twitter
3 tweeters

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
4 Mendeley
Summary Policy documents Twitter Dimensions citations
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Chapter title
Evaluating Input Perturbation Methods for Interpreting CNNs and Saliency Map Comparison
Book title
Computer Vision – ECCV 2020 Workshops
Published in
arXiv, January 2021
DOI 10.1007/978-3-030-66415-2_8
Book ISBNs
978-3-03-066414-5, 978-3-03-066415-2
Authors

Lukas Brunke, Prateek Agrawal, Nikhil George, Brunke, Lukas, Agrawal, Prateek, George, Nikhil

View on publisher site

Twitter Demographics

The data shown below were collected from the profiles of 3 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 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 %
Professor > Associate Professor 1 25%
Student > Doctoral Student 1 25%
Student > Master 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 1 25%
Engineering 1 25%
Unknown 2 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 26 January 2022.
All research outputs
#6,371,364
of 23,511,526 outputs
Outputs from arXiv
#133,519
of 972,877 outputs
Outputs of similar age
#155,331
of 504,395 outputs
Outputs of similar age from arXiv
#4,574
of 31,679 outputs
Altmetric has tracked 23,511,526 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 972,877 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 86% of its peers.
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 504,395 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 31,679 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.

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