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Assessing the potential for deep learning and computer vision to identify bumble bee species from images

Overview of attention for article published in Scientific Reports, April 2021
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

twitter
53 X users
facebook
1 Facebook page

Citations

dimensions_citation
46 Dimensions

Readers on

mendeley
88 Mendeley
Title
Assessing the potential for deep learning and computer vision to identify bumble bee species from images
Published in
Scientific Reports, April 2021
DOI 10.1038/s41598-021-87210-1
Pubmed ID
Authors

Brian J. Spiesman, Claudio Gratton, Richard G. Hatfield, William H. Hsu, Sarina Jepsen, Brian McCornack, Krushi Patel, Guanghui Wang

X Demographics

X Demographics

The data shown below were collected from the profiles of 53 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 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 88 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 17%
Researcher 12 14%
Student > Master 11 13%
Other 4 5%
Professor 4 5%
Other 8 9%
Unknown 34 39%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 32%
Computer Science 7 8%
Environmental Science 5 6%
Engineering 4 5%
Mathematics 1 1%
Other 6 7%
Unknown 37 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 37. 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 17 September 2022.
All research outputs
#1,053,699
of 24,835,862 outputs
Outputs from Scientific Reports
#10,741
of 135,925 outputs
Outputs of similar age
#28,745
of 433,694 outputs
Outputs of similar age from Scientific Reports
#332
of 4,623 outputs
Altmetric has tracked 24,835,862 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 135,925 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.7. This one has done particularly well, scoring higher than 92% 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 433,694 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 93% of its contemporaries.
We're also able to compare this research output to 4,623 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 92% of its contemporaries.