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KECANet: A novel convolutional kernel network for ocean SAR scene classification with limited labeled data

Overview of attention for article published in Frontiers in Marine Science, September 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
6 X users

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
2 Mendeley
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Title
KECANet: A novel convolutional kernel network for ocean SAR scene classification with limited labeled data
Published in
Frontiers in Marine Science, September 2022
DOI 10.3389/fmars.2022.935600
Authors

Ming Ma, Chengzu Bai, Shuo Zhang, Longxia Qian, Hengqian Yan

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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 50%
Unknown 1 50%
Readers by discipline Count As %
Arts and Humanities 1 50%
Unknown 1 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 12 March 2024.
All research outputs
#14,453,127
of 25,473,687 outputs
Outputs from Frontiers in Marine Science
#4,766
of 10,785 outputs
Outputs of similar age
#170,024
of 433,251 outputs
Outputs of similar age from Frontiers in Marine Science
#240
of 788 outputs
Altmetric has tracked 25,473,687 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,785 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has gotten more attention than average, scoring higher than 55% of its peers.
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 433,251 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 788 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.