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High-throughput soybean seeds phenotyping with convolutional neural networks and transfer learning

Overview of attention for article published in Plant Methods, May 2021
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)

Mentioned by

twitter
8 tweeters

Readers on

mendeley
23 Mendeley
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Title
High-throughput soybean seeds phenotyping with convolutional neural networks and transfer learning
Published in
Plant Methods, May 2021
DOI 10.1186/s13007-021-00749-y
Pubmed ID
Authors

Si Yang, Lihua Zheng, Peng He, Tingting Wu, Shi Sun, Minjuan Wang

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 17%
Researcher 3 13%
Student > Ph. D. Student 3 13%
Student > Bachelor 2 9%
Student > Doctoral Student 2 9%
Other 1 4%
Unknown 8 35%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 39%
Computer Science 5 22%
Biochemistry, Genetics and Molecular Biology 1 4%
Physics and Astronomy 1 4%
Chemistry 1 4%
Other 0 0%
Unknown 6 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 07 July 2021.
All research outputs
#6,115,200
of 22,489,892 outputs
Outputs from Plant Methods
#363
of 1,058 outputs
Outputs of similar age
#114,438
of 344,413 outputs
Outputs of similar age from Plant Methods
#1
of 1 outputs
Altmetric has tracked 22,489,892 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,058 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has gotten more attention than average, scoring higher than 65% 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 344,413 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 66% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them