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Deep learning‐based methods for individual recognition in small birds

Overview of attention for article published in Methods in Ecology and Evolution, July 2020
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#6 of 2,539)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Readers on

mendeley
258 Mendeley
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Title
Deep learning‐based methods for individual recognition in small birds
Published in
Methods in Ecology and Evolution, July 2020
DOI 10.1111/2041-210x.13436
Authors

André C. Ferreira, Liliana R. Silva, Francesco Renna, Hanja B. Brandl, Julien P. Renoult, Damien R. Farine, Rita Covas, Claire Doutrelant

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 224 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 258 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 258 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 48 19%
Researcher 38 15%
Student > Master 31 12%
Student > Bachelor 27 10%
Other 9 3%
Other 31 12%
Unknown 74 29%
Readers by discipline Count As %
Agricultural and Biological Sciences 73 28%
Environmental Science 30 12%
Computer Science 22 9%
Biochemistry, Genetics and Molecular Biology 6 2%
Engineering 6 2%
Other 28 11%
Unknown 93 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 487. 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 07 January 2024.
All research outputs
#58,405
of 26,316,852 outputs
Outputs from Methods in Ecology and Evolution
#6
of 2,539 outputs
Outputs of similar age
#2,114
of 432,202 outputs
Outputs of similar age from Methods in Ecology and Evolution
#1
of 56 outputs
Altmetric has tracked 26,316,852 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,539 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 24.9. This one has done particularly well, scoring higher than 99% 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 432,202 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.