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Farmland boundary extraction based on the AttMobile-DeeplabV3+ network and least squares fitting of straight lines

Overview of attention for article published in Frontiers in Plant Science, August 2023
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1 X user

Readers on

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3 Mendeley
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Title
Farmland boundary extraction based on the AttMobile-DeeplabV3+ network and least squares fitting of straight lines
Published in
Frontiers in Plant Science, August 2023
DOI 10.3389/fpls.2023.1228590
Pubmed ID
Authors

Hao Lu, Hao Wang, Zhifeng Ma, Yaxin Ren, Weiqiang Fu, Yongchao Shan, Shupeng Hu, Guangqiang Zhang, Zhijun Meng

Timeline

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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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Student > Master 1 33%
Unknown 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Agricultural and Biological Sciences 1 33%
Unknown 1 33%
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 18 August 2023.
All research outputs
#21,765,130
of 24,287,697 outputs
Outputs from Frontiers in Plant Science
#18,364
of 22,802 outputs
Outputs of similar age
#126,208
of 155,719 outputs
Outputs of similar age from Frontiers in Plant Science
#251
of 450 outputs
Altmetric has tracked 24,287,697 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 22,802 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 155,719 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 450 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.