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Tomato Diseases and Pests Detection Based on Improved Yolo V3 Convolutional Neural Network

Overview of attention for article published in Frontiers in Plant Science, June 2020
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Mentioned by

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1 X user

Citations

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298 Dimensions

Readers on

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412 Mendeley
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Title
Tomato Diseases and Pests Detection Based on Improved Yolo V3 Convolutional Neural Network
Published in
Frontiers in Plant Science, June 2020
DOI 10.3389/fpls.2020.00898
Pubmed ID
Authors

Jun Liu, Xuewei Wang

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 412 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 412 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 41 10%
Student > Ph. D. Student 35 8%
Student > Bachelor 26 6%
Researcher 22 5%
Lecturer 13 3%
Other 39 9%
Unknown 236 57%
Readers by discipline Count As %
Computer Science 69 17%
Agricultural and Biological Sciences 39 9%
Engineering 37 9%
Biochemistry, Genetics and Molecular Biology 5 1%
Mathematics 3 <1%
Other 15 4%
Unknown 244 59%
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 22 July 2020.
All research outputs
#22,556,421
of 25,163,238 outputs
Outputs from Frontiers in Plant Science
#19,421
of 24,162 outputs
Outputs of similar age
#324,814
of 378,010 outputs
Outputs of similar age from Frontiers in Plant Science
#516
of 566 outputs
Altmetric has tracked 25,163,238 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 24,162 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 378,010 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 566 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.