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Unsupervised Bayesian learning for rice panicle segmentation with UAV images

Overview of attention for article published in Plant Methods, February 2020
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Mentioned by

twitter
2 tweeters

Citations

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8 Dimensions

Readers on

mendeley
29 Mendeley
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Title
Unsupervised Bayesian learning for rice panicle segmentation with UAV images
Published in
Plant Methods, February 2020
DOI 10.1186/s13007-020-00567-8
Pubmed ID
Authors

Md Abul Hayat, Jingxian Wu, Yingli Cao

Twitter Demographics

The data shown below were collected from the profiles of 2 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 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 17%
Researcher 4 14%
Lecturer 2 7%
Student > Doctoral Student 2 7%
Student > Master 2 7%
Other 2 7%
Unknown 12 41%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 24%
Computer Science 6 21%
Engineering 2 7%
Unknown 14 48%

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 10 September 2020.
All research outputs
#18,714,452
of 23,195,584 outputs
Outputs from Plant Methods
#968
of 1,096 outputs
Outputs of similar age
#269,655
of 361,698 outputs
Outputs of similar age from Plant Methods
#39
of 40 outputs
Altmetric has tracked 23,195,584 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,096 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 3rd percentile – i.e., 3% 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 361,698 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 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.