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Learning Grammars for Architecture-Specific Facade Parsing

Overview of attention for article published in International Journal of Computer Vision, March 2016
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

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1 X user

Citations

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39 Dimensions

Readers on

mendeley
41 Mendeley
Title
Learning Grammars for Architecture-Specific Facade Parsing
Published in
International Journal of Computer Vision, March 2016
DOI 10.1007/s11263-016-0887-4
Authors

Raghudeep Gadde, Renaud Marlet, Nikos Paragios

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

Geographical breakdown

Country Count As %
China 1 2%
Luxembourg 1 2%
Unknown 39 95%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 22%
Student > Ph. D. Student 9 22%
Researcher 4 10%
Other 3 7%
Student > Doctoral Student 3 7%
Other 2 5%
Unknown 11 27%
Readers by discipline Count As %
Computer Science 15 37%
Design 5 12%
Mathematics 3 7%
Engineering 3 7%
Earth and Planetary Sciences 1 2%
Other 3 7%
Unknown 11 27%
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 16 May 2016.
All research outputs
#15,373,286
of 22,870,727 outputs
Outputs from International Journal of Computer Vision
#869
of 1,155 outputs
Outputs of similar age
#177,120
of 298,418 outputs
Outputs of similar age from International Journal of Computer Vision
#4
of 5 outputs
Altmetric has tracked 22,870,727 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 1,155 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 12th percentile – i.e., 12% 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 298,418 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.