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A Convolutional Neural Network Bird Species Recognizer Built From Little Data by Iteratively Training, Detecting, and Labeling

Overview of attention for article published in Frontiers in Ecology and Evolution, March 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

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7 Dimensions

Readers on

mendeley
23 Mendeley
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Title
A Convolutional Neural Network Bird Species Recognizer Built From Little Data by Iteratively Training, Detecting, and Labeling
Published in
Frontiers in Ecology and Evolution, March 2022
DOI 10.3389/fevo.2022.810330
Authors

Philip Eichinski, Callan Alexander, Paul Roe, Stuart Parsons, Susan Fuller

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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer > Senior Lecturer 2 9%
Other 2 9%
Student > Ph. D. Student 2 9%
Student > Doctoral Student 1 4%
Lecturer 1 4%
Other 2 9%
Unknown 13 57%
Readers by discipline Count As %
Engineering 3 13%
Computer Science 2 9%
Arts and Humanities 1 4%
Agricultural and Biological Sciences 1 4%
Environmental Science 1 4%
Other 2 9%
Unknown 13 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 18 March 2022.
All research outputs
#14,307,901
of 23,371,053 outputs
Outputs from Frontiers in Ecology and Evolution
#2,375
of 4,368 outputs
Outputs of similar age
#208,942
of 443,009 outputs
Outputs of similar age from Frontiers in Ecology and Evolution
#165
of 357 outputs
Altmetric has tracked 23,371,053 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,368 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.5. This one is in the 43rd percentile – i.e., 43% 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 443,009 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 51% of its contemporaries.
We're also able to compare this research output to 357 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 50% of its contemporaries.