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A survey on generative adversarial networks for imbalance problems in computer vision tasks

Overview of attention for article published in Journal of Big Data, January 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
10 X users
patent
1 patent

Citations

dimensions_citation
120 Dimensions

Readers on

mendeley
252 Mendeley
Title
A survey on generative adversarial networks for imbalance problems in computer vision tasks
Published in
Journal of Big Data, January 2021
DOI 10.1186/s40537-021-00414-0
Pubmed ID
Authors

Vignesh Sampath, Iñaki Maurtua, Juan José Aguilar Martín, Aitor Gutierrez

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 252 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 252 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 50 20%
Researcher 16 6%
Lecturer 15 6%
Student > Master 15 6%
Student > Doctoral Student 12 5%
Other 39 15%
Unknown 105 42%
Readers by discipline Count As %
Computer Science 67 27%
Engineering 31 12%
Unspecified 8 3%
Business, Management and Accounting 5 2%
Medicine and Dentistry 4 2%
Other 26 10%
Unknown 111 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 27 May 2022.
All research outputs
#3,832,846
of 23,860,205 outputs
Outputs from Journal of Big Data
#71
of 359 outputs
Outputs of similar age
#101,687
of 509,237 outputs
Outputs of similar age from Journal of Big Data
#5
of 21 outputs
Altmetric has tracked 23,860,205 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 359 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.6. This one has done well, scoring higher than 80% 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 509,237 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 21 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.