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Microstructure quality control of steels using deep learning

Overview of attention for article published in Frontiers in Materials, August 2023
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#43 of 2,883)
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
1 news outlet
twitter
1 X user

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
5 Mendeley
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Title
Microstructure quality control of steels using deep learning
Published in
Frontiers in Materials, August 2023
DOI 10.3389/fmats.2023.1222456
Authors

Ali Riza Durmaz, Sai Teja Potu, Daniel Romich, Johannes J. Möller, Ralf Nützel

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 > Ph. D. Student 1 20%
Other 1 20%
Unknown 3 60%
Readers by discipline Count As %
Engineering 1 20%
Unknown 4 80%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 05 October 2023.
All research outputs
#3,129,944
of 24,565,648 outputs
Outputs from Frontiers in Materials
#43
of 2,883 outputs
Outputs of similar age
#47,615
of 330,253 outputs
Outputs of similar age from Frontiers in Materials
#1
of 123 outputs
Altmetric has tracked 24,565,648 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,883 research outputs from this source. They receive a mean Attention Score of 1.6. This one has done particularly well, scoring higher than 98% 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 330,253 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 123 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.