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Scene Particles: Unregularized Particle-Based Scene Flow Estimation

Overview of attention for article published in IEEE Transactions on Software Engineering, February 2014
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

twitter
1 X user
patent
4 patents

Readers on

mendeley
56 Mendeley
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Article details
Title
Scene Particles: Unregularized Particle-Based Scene Flow Estimation
Published in
IEEE Transactions on Software Engineering, February 2014
DOI 10.1109/tpami.2013.162
Pubmed ID
Authors

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Timeline Attention over time Attention Score history
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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 demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Geographical breakdown
Country Count As %
United States 2 4%
Japan 2 4%
United Kingdom 1 2%
Unknown 51 91%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 22 39%
Student > Master 7 13%
Researcher 7 13%
Professor > Associate Professor 4 7%
Student > Bachelor 3 5%
Other 5 9%
Unknown 8 14%
Readers by discipline
Readers by discipline Count As %
Computer Science 29 52%
Engineering 15 27%
Mathematics 1 2%
Biochemistry, Genetics and Molecular Biology 1 2%
Unknown 10 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 April 2022.
All research outputs
#7,439,169
of 34,364,397 outputs
Outputs from IEEE Transactions on Software Engineering
#1,890
of 7,909 outputs
Outputs of similar age
#73,535
of 374,307 outputs
Outputs of similar age from IEEE Transactions on Software Engineering
#8
of 40 outputs
Altmetric has tracked 34,364,397 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,909 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one has done well, scoring higher than 75% 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 374,307 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 80% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.