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A few-shot learning method for tobacco abnormality identification

Overview of attention for article published in Frontiers in Plant Science, March 2024
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

twitter
8 X users

Readers on

mendeley
1 Mendeley
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Title
A few-shot learning method for tobacco abnormality identification
Published in
Frontiers in Plant Science, March 2024
DOI 10.3389/fpls.2024.1333236
Pubmed ID
Authors

Hong Lin, Zhenping Qiang, Rita Tse, Su-Kit Tang, Giovanni Pau

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 100%
Readers by discipline Count As %
Unspecified 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 22 April 2024.
All research outputs
#14,880,027
of 25,808,886 outputs
Outputs from Frontiers in Plant Science
#6,670
of 24,936 outputs
Outputs of similar age
#96,021
of 266,786 outputs
Outputs of similar age from Frontiers in Plant Science
#63
of 459 outputs
Altmetric has tracked 25,808,886 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,936 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 71% 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 266,786 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 63% of its contemporaries.
We're also able to compare this research output to 459 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.