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An innovative methodology for detection and quantification of cracks through incorporation of depth perception

Overview of attention for article published in Machine Vision & Applications, December 2011
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
83 Dimensions

Readers on

mendeley
111 Mendeley
citeulike
1 CiteULike
Title
An innovative methodology for detection and quantification of cracks through incorporation of depth perception
Published in
Machine Vision & Applications, December 2011
DOI 10.1007/s00138-011-0394-0
Authors

Mohammad R. Jahanshahi, Sami F. Masri, Curtis W. Padgett, Gaurav S. Sukhatme

Mendeley readers

The data shown below were compiled from readership statistics for 111 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 <1%
Malaysia 1 <1%
United Kingdom 1 <1%
Brazil 1 <1%
Colombia 1 <1%
Greece 1 <1%
Unknown 105 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 35 32%
Student > Master 26 23%
Researcher 14 13%
Unspecified 9 8%
Student > Doctoral Student 8 7%
Other 19 17%
Readers by discipline Count As %
Engineering 68 61%
Computer Science 21 19%
Unspecified 14 13%
Psychology 4 4%
Physics and Astronomy 2 2%
Other 2 2%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 21 May 2015.
All research outputs
#2,496,782
of 9,370,416 outputs
Outputs from Machine Vision & Applications
#15
of 72 outputs
Outputs of similar age
#33,379
of 98,865 outputs
Outputs of similar age from Machine Vision & Applications
#1
of 1 outputs
Altmetric has tracked 9,370,416 research outputs across all sources so far. This one has received more attention than most of these and is in the 59th percentile.
So far Altmetric has tracked 72 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 51% 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 98,865 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them