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Deep learning-based classification of high intensity light patterns in photorefractive crystals

Overview of attention for article published in Journal of Optics, February 2020
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Deep learning-based classification of high intensity light patterns in photorefractive crystals
Published in
Journal of Optics, February 2020
DOI 10.1088/2040-8986/ab70f0
Authors

Marija Ivanovi, Ana Mani, Carla Hermann-Avigliano, Ljupo Hadievski, Aleksandra Maluckov

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 29%
Professor > Associate Professor 1 14%
Unknown 4 57%
Readers by discipline Count As %
Physics and Astronomy 1 14%
Materials Science 1 14%
Unknown 5 71%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 23 February 2020.
All research outputs
#16,057,393
of 25,387,668 outputs
Outputs from Journal of Optics
#574
of 1,213 outputs
Outputs of similar age
#267,967
of 476,320 outputs
Outputs of similar age from Journal of Optics
#2
of 10 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,213 research outputs from this source. They receive a mean Attention Score of 3.3. This one has gotten more attention than average, scoring higher than 50% 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 476,320 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.