↓ Skip to main content

Use of Neural Signals to Evaluate the Quality of Generative Adversarial Network Performance in Facial Image Generation

Overview of attention for article published in Cognitive Computation, August 2019
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#4 of 344)
  • High Attention Score compared to outputs of the same age (80th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

twitter
20 tweeters

Readers on

mendeley
10 Mendeley
Title
Use of Neural Signals to Evaluate the Quality of Generative Adversarial Network Performance in Facial Image Generation
Published in
Cognitive Computation, August 2019
DOI 10.1007/s12559-019-09670-y
Authors

Zhengwei Wang, Graham Healy, Alan F. Smeaton, Tomás E. Ward

Twitter Demographics

The data shown below were collected from the profiles of 20 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 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 20%
Student > Master 2 20%
Student > Ph. D. Student 2 20%
Student > Bachelor 1 10%
Student > Doctoral Student 1 10%
Other 0 0%
Unknown 2 20%
Readers by discipline Count As %
Computer Science 6 60%
Psychology 1 10%
Engineering 1 10%
Unknown 2 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 16 September 2019.
All research outputs
#1,697,398
of 14,033,278 outputs
Outputs from Cognitive Computation
#4
of 344 outputs
Outputs of similar age
#61,883
of 310,887 outputs
Outputs of similar age from Cognitive Computation
#2
of 7 outputs
Altmetric has tracked 14,033,278 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 344 research outputs from this source. They receive a mean Attention Score of 1.4. This one has done particularly well, scoring higher than 98% 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 310,887 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.