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An improved convolutional neural network for convenient rail damage detection

Overview of attention for article published in Frontiers in Energy Research, September 2022
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1 X user

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8 Mendeley
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Title
An improved convolutional neural network for convenient rail damage detection
Published in
Frontiers in Energy Research, September 2022
DOI 10.3389/fenrg.2022.1007188
Authors

Zhongzhou Zhang, Xinhao Che, Yan Song

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

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 25%
Student > Ph. D. Student 1 13%
Other 1 13%
Unknown 4 50%
Readers by discipline Count As %
Computer Science 2 25%
Engineering 2 25%
Unknown 4 50%
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 14 October 2022.
All research outputs
#20,897,310
of 23,523,017 outputs
Outputs from Frontiers in Energy Research
#1,358
of 3,579 outputs
Outputs of similar age
#346,030
of 433,760 outputs
Outputs of similar age from Frontiers in Energy Research
#50
of 335 outputs
Altmetric has tracked 23,523,017 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 3,579 research outputs from this source. They receive a mean Attention Score of 1.7. 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 433,760 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 335 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.