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Disaster cassification net: A disaster classification algorithm on remote sensing imagery

Overview of attention for article published in Frontiers in Environmental Science, January 2023
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Mentioned by

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1 X user

Citations

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2 Dimensions

Readers on

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5 Mendeley
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Title
Disaster cassification net: A disaster classification algorithm on remote sensing imagery
Published in
Frontiers in Environmental Science, January 2023
DOI 10.3389/fenvs.2022.1095986
Authors

Jianye Yuan, Xinwang Ding, Fangyuan Liu, Xin Cai

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

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 40%
Other 1 20%
Unknown 2 40%
Readers by discipline Count As %
Business, Management and Accounting 1 20%
Medicine and Dentistry 1 20%
Engineering 1 20%
Unknown 2 40%
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 04 February 2023.
All research outputs
#20,687,221
of 23,283,373 outputs
Outputs from Frontiers in Environmental Science
#2,034
of 3,570 outputs
Outputs of similar age
#329,568
of 419,948 outputs
Outputs of similar age from Frontiers in Environmental Science
#93
of 385 outputs
Altmetric has tracked 23,283,373 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 3,570 research outputs from this source. They receive a mean Attention Score of 4.5. 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 419,948 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 385 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.