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Plant recognition by AI: Deep neural nets, transformers, and kNN in deep embeddings

Overview of attention for article published in Frontiers in Plant Science, September 2022
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Mentioned by

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2 X users

Citations

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11 Dimensions

Readers on

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43 Mendeley
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Title
Plant recognition by AI: Deep neural nets, transformers, and kNN in deep embeddings
Published in
Frontiers in Plant Science, September 2022
DOI 10.3389/fpls.2022.787527
Pubmed ID
Authors

Lukáš Picek, Milan Šulc, Yash Patel, Jiří Matas

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 4 9%
Student > Ph. D. Student 4 9%
Student > Master 4 9%
Lecturer 3 7%
Researcher 3 7%
Other 5 12%
Unknown 20 47%
Readers by discipline Count As %
Computer Science 7 16%
Unspecified 4 9%
Engineering 4 9%
Environmental Science 2 5%
Agricultural and Biological Sciences 2 5%
Other 4 9%
Unknown 20 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 28 September 2022.
All research outputs
#19,730,950
of 24,248,886 outputs
Outputs from Frontiers in Plant Science
#15,505
of 22,721 outputs
Outputs of similar age
#309,908
of 425,634 outputs
Outputs of similar age from Frontiers in Plant Science
#884
of 1,438 outputs
Altmetric has tracked 24,248,886 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,721 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 19th percentile – i.e., 19% 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 425,634 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,438 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.