↓ Skip to main content

Probabilistic Noise2Void: Unsupervised Content-Aware Denoising

Overview of attention for article published in arXiv, February 2020
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

twitter
107 X users
patent
1 patent

Citations

dimensions_citation
108 Dimensions

Readers on

mendeley
184 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Probabilistic Noise2Void: Unsupervised Content-Aware Denoising
Published in
arXiv, February 2020
DOI 10.3389/fcomp.2020.00005
Authors

Alexander Krull, Tomáš Vičar, Mangal Prakash, Manan Lalit, Florian Jug

X Demographics

X Demographics

The data shown below were collected from the profiles of 107 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 184 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 184 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 19%
Researcher 31 17%
Student > Master 24 13%
Student > Doctoral Student 12 7%
Other 10 5%
Other 16 9%
Unknown 56 30%
Readers by discipline Count As %
Computer Science 36 20%
Engineering 30 16%
Physics and Astronomy 19 10%
Agricultural and Biological Sciences 11 6%
Biochemistry, Genetics and Molecular Biology 9 5%
Other 16 9%
Unknown 63 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 65. 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 02 March 2023.
All research outputs
#661,813
of 25,584,565 outputs
Outputs from arXiv
#8,219
of 930,683 outputs
Outputs of similar age
#16,765
of 384,216 outputs
Outputs of similar age from arXiv
#228
of 21,083 outputs
Altmetric has tracked 25,584,565 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 930,683 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 99% 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 384,216 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 21,083 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 98% of its contemporaries.