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A Novel Federated Learning Scheme for Generative Adversarial Networks

Overview of attention for article published in IEEE Transactions on Mobile Computing, May 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)

Mentioned by

patent
1 patent

Readers on

mendeley
5 Mendeley
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Title
A Novel Federated Learning Scheme for Generative Adversarial Networks
Published in
IEEE Transactions on Mobile Computing, May 2023
DOI 10.1109/tmc.2023.3278668
Authors

Jiaxin Zhang, Liang Zhao, Keping Yu, Geyong Min, Ahmed Y. Al-Dubai, Albert Y. Zomaya

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 20%
Other 1 20%
Unknown 3 60%
Readers by discipline Count As %
Unspecified 1 20%
Physics and Astronomy 1 20%
Unknown 3 60%
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 20 July 2021.
All research outputs
#8,543,833
of 25,394,764 outputs
Outputs from IEEE Transactions on Mobile Computing
#254
of 788 outputs
Outputs of similar age
#140,552
of 388,234 outputs
Outputs of similar age from IEEE Transactions on Mobile Computing
#1
of 2 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 788 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 18th percentile – i.e., 18% of its peers scored the same or lower than it.
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 388,234 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 61% of its contemporaries.
We're also able to compare this research output to 2 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