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Attacking convolutional neural network using differential evolution

Overview of attention for article published in IPSJ Transactions on Computer Vision and Applications, February 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (54th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
48 Dimensions

Readers on

mendeley
64 Mendeley
Title
Attacking convolutional neural network using differential evolution
Published in
IPSJ Transactions on Computer Vision and Applications, February 2019
DOI 10.1186/s41074-019-0053-3
Authors

Jiawei Su, Danilo Vasconcellos Vargas, Kouichi Sakurai

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 20%
Student > Master 9 14%
Student > Bachelor 7 11%
Researcher 7 11%
Student > Postgraduate 4 6%
Other 9 14%
Unknown 15 23%
Readers by discipline Count As %
Computer Science 36 56%
Engineering 5 8%
Physics and Astronomy 2 3%
Business, Management and Accounting 1 2%
Mathematics 1 2%
Other 1 2%
Unknown 18 28%
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 13 January 2022.
All research outputs
#7,480,713
of 22,867,327 outputs
Outputs from IPSJ Transactions on Computer Vision and Applications
#14
of 33 outputs
Outputs of similar age
#142,179
of 352,149 outputs
Outputs of similar age from IPSJ Transactions on Computer Vision and Applications
#1
of 1 outputs
Altmetric has tracked 22,867,327 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 33 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one scored the same or higher as 19 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 352,149 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 54% of its contemporaries.
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