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Retrieving 2D shapes using caterpillar decomposition

Overview of attention for article published in Machine Vision and Applications, January 2012
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Mentioned by

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1 X user

Citations

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6 Dimensions

Readers on

mendeley
6 Mendeley
Title
Retrieving 2D shapes using caterpillar decomposition
Published in
Machine Vision and Applications, January 2012
DOI 10.1007/s00138-012-0406-8
Authors

M. Fatih Demirci

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

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 33%
Professor 1 17%
Student > Doctoral Student 1 17%
Student > Ph. D. Student 1 17%
Student > Postgraduate 1 17%
Other 0 0%
Readers by discipline Count As %
Computer Science 4 67%
Medicine and Dentistry 1 17%
Engineering 1 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 May 2012.
All research outputs
#16,031,680
of 23,794,258 outputs
Outputs from Machine Vision and Applications
#374
of 551 outputs
Outputs of similar age
#168,063
of 250,837 outputs
Outputs of similar age from Machine Vision and Applications
#11
of 11 outputs
Altmetric has tracked 23,794,258 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 551 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 20th percentile – i.e., 20% 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 250,837 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 22nd percentile – i.e., 22% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.