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Real-time gradient vector flow on GPUs using OpenCL

Overview of attention for article published in Journal of Real-Time Image Processing, June 2012
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Mentioned by

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2 X users

Citations

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20 Dimensions

Readers on

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19 Mendeley
Title
Real-time gradient vector flow on GPUs using OpenCL
Published in
Journal of Real-Time Image Processing, June 2012
DOI 10.1007/s11554-012-0257-6
Authors

Erik Smistad, Anne C. Elster, Frank Lindseth

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

Geographical breakdown

Country Count As %
Germany 1 5%
Norway 1 5%
Unknown 17 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 42%
Researcher 4 21%
Student > Bachelor 3 16%
Student > Master 2 11%
Student > Doctoral Student 1 5%
Other 0 0%
Unknown 1 5%
Readers by discipline Count As %
Computer Science 6 32%
Physics and Astronomy 5 26%
Engineering 4 21%
Earth and Planetary Sciences 1 5%
Neuroscience 1 5%
Other 1 5%
Unknown 1 5%
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 10 June 2012.
All research outputs
#13,666,300
of 22,668,244 outputs
Outputs from Journal of Real-Time Image Processing
#93
of 128 outputs
Outputs of similar age
#95,173
of 166,809 outputs
Outputs of similar age from Journal of Real-Time Image Processing
#2
of 2 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 128 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 25th percentile – i.e., 25% 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 166,809 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.