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A Method of Green Citrus Detection in Natural Environments Using a Deep Convolutional Neural Network

Overview of attention for article published in Frontiers in Plant Science, September 2021
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Citations

dimensions_citation
23 Dimensions

Readers on

mendeley
18 Mendeley
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Title
A Method of Green Citrus Detection in Natural Environments Using a Deep Convolutional Neural Network
Published in
Frontiers in Plant Science, September 2021
DOI 10.3389/fpls.2021.705737
Pubmed ID
Authors

Zhenhui Zheng, Juntao Xiong, Huan Lin, Yonglin Han, Baoxia Sun, Zhiming Xie, Zhengang Yang, Chenglin Wang

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 11%
Student > Ph. D. Student 1 6%
Unknown 15 83%
Readers by discipline Count As %
Unspecified 2 11%
Agricultural and Biological Sciences 1 6%
Unknown 15 83%
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 25 September 2021.
All research outputs
#16,904,913
of 24,858,211 outputs
Outputs from Frontiers in Plant Science
#12,527
of 23,758 outputs
Outputs of similar age
#255,668
of 422,490 outputs
Outputs of similar age from Frontiers in Plant Science
#471
of 873 outputs
Altmetric has tracked 24,858,211 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 23,758 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 41st percentile – i.e., 41% 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 422,490 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 873 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.