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Application of Three Deep Learning Schemes Into Oceanic Eddy Detection

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

Mentioned by

twitter
6 X users

Citations

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18 Dimensions

Readers on

mendeley
17 Mendeley
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Title
Application of Three Deep Learning Schemes Into Oceanic Eddy Detection
Published in
Frontiers in Marine Science, June 2021
DOI 10.3389/fmars.2021.672334
Authors

Guangjun Xu, Wenhong Xie, Changming Dong, Xiaoqian Gao

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 12%
Student > Master 2 12%
Student > Postgraduate 2 12%
Researcher 2 12%
Student > Ph. D. Student 1 6%
Other 2 12%
Unknown 6 35%
Readers by discipline Count As %
Earth and Planetary Sciences 4 24%
Engineering 2 12%
Physics and Astronomy 2 12%
Computer Science 1 6%
Unspecified 1 6%
Other 1 6%
Unknown 6 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 21 June 2021.
All research outputs
#15,030,956
of 23,885,338 outputs
Outputs from Frontiers in Marine Science
#5,355
of 9,480 outputs
Outputs of similar age
#229,432
of 433,551 outputs
Outputs of similar age from Frontiers in Marine Science
#372
of 569 outputs
Altmetric has tracked 23,885,338 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 9,480 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.9. This one is in the 40th percentile – i.e., 40% 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 433,551 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 569 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.