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Assessment of Convolutional Neural Network Architectures for Earthquake-Induced Building Damage Detection based on Pre- and Post-Event Orthophoto Images

Overview of attention for article published in Remote Sensing, October 2020
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
4 X users

Citations

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37 Dimensions

Readers on

mendeley
67 Mendeley
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Title
Assessment of Convolutional Neural Network Architectures for Earthquake-Induced Building Damage Detection based on Pre- and Post-Event Orthophoto Images
Published in
Remote Sensing, October 2020
DOI 10.3390/rs12213529
Authors

Bahareh Kalantar, Naonori Ueda, Husam A. H. Al-Najjar, Alfian Abdul Halin

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 19%
Student > Ph. D. Student 10 15%
Lecturer 5 7%
Student > Doctoral Student 4 6%
Researcher 4 6%
Other 6 9%
Unknown 25 37%
Readers by discipline Count As %
Engineering 13 19%
Computer Science 12 18%
Earth and Planetary Sciences 5 7%
Environmental Science 3 4%
Social Sciences 2 3%
Other 4 6%
Unknown 28 42%
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 04 August 2021.
All research outputs
#13,651,377
of 23,270,775 outputs
Outputs from Remote Sensing
#4,289
of 11,639 outputs
Outputs of similar age
#205,343
of 420,611 outputs
Outputs of similar age from Remote Sensing
#236
of 740 outputs
Altmetric has tracked 23,270,775 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,639 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 61% 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 420,611 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 50% of its contemporaries.
We're also able to compare this research output to 740 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 66% of its contemporaries.