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Token-Selective Vision Transformer for fine-grained image recognition of marine organisms

Overview of attention for article published in Frontiers in Marine Science, April 2023
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Token-Selective Vision Transformer for fine-grained image recognition of marine organisms
Published in
Frontiers in Marine Science, April 2023
DOI 10.3389/fmars.2023.1174347
Authors

Guangzhe Si, Ying Xiao, Bin Wei, Leon Bevan Bullock, Yueyue Wang, Xiaodong Wang

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Professor 1 14%
Researcher 1 14%
Lecturer 1 14%
Unknown 4 57%
Readers by discipline Count As %
Computer Science 1 14%
Medicine and Dentistry 1 14%
Engineering 1 14%
Unknown 4 57%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 25 April 2023.
All research outputs
#15,204,763
of 24,137,933 outputs
Outputs from Frontiers in Marine Science
#5,516
of 9,679 outputs
Outputs of similar age
#196,099
of 389,825 outputs
Outputs of similar age from Frontiers in Marine Science
#212
of 593 outputs
Altmetric has tracked 24,137,933 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,679 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 38th percentile – i.e., 38% 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 389,825 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 593 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.