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Cotton plant part 3D segmentation and architectural trait extraction using point voxel convolutional neural networks

Overview of attention for article published in Plant Methods, March 2023
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (57th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
5 X users

Citations

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3 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Cotton plant part 3D segmentation and architectural trait extraction using point voxel convolutional neural networks
Published in
Plant Methods, March 2023
DOI 10.1186/s13007-023-00996-1
Pubmed ID
Authors

Farah Saeed, Shangpeng Sun, Javier Rodriguez-Sanchez, John Snider, Tianming Liu, Changying Li

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 14%
Student > Master 1 14%
Unknown 5 71%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 29%
Unknown 5 71%
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 19 April 2023.
All research outputs
#14,840,825
of 25,744,802 outputs
Outputs from Plant Methods
#672
of 1,285 outputs
Outputs of similar age
#175,379
of 424,331 outputs
Outputs of similar age from Plant Methods
#21
of 32 outputs
Altmetric has tracked 25,744,802 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 1,285 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one is in the 46th percentile – i.e., 46% 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 424,331 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 57% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.