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TeaDiseaseNet: multi-scale self-attentive tea disease detection

Overview of attention for article published in Frontiers in Plant Science, October 2023
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Mentioned by

twitter
1 X user

Readers on

mendeley
4 Mendeley
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Title
TeaDiseaseNet: multi-scale self-attentive tea disease detection
Published in
Frontiers in Plant Science, October 2023
DOI 10.3389/fpls.2023.1257212
Pubmed ID
Authors

Yange Sun, Fei Wu, Huaping Guo, Ran Li, Jianfeng Yao, Jianbo Shen

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Unspecified 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Unspecified 1 25%
Unknown 1 25%
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 11 October 2023.
All research outputs
#22,047,018
of 24,598,501 outputs
Outputs from Frontiers in Plant Science
#18,710
of 23,345 outputs
Outputs of similar age
#138,186
of 170,551 outputs
Outputs of similar age from Frontiers in Plant Science
#260
of 460 outputs
Altmetric has tracked 24,598,501 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 23,345 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 1st percentile – i.e., 1% 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 170,551 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 460 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.