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Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation

Overview of attention for article published in International Journal of Computer Vision, February 2012
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

patent
4 patents

Citations

dimensions_citation
273 Dimensions

Readers on

mendeley
245 Mendeley
Title
Creating Large-Scale City Models from 3D-Point Clouds: A Robust Approach with Hybrid Representation
Published in
International Journal of Computer Vision, February 2012
DOI 10.1007/s11263-012-0517-8
Authors

Florent Lafarge, Clément Mallet

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 245 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 4 2%
Germany 2 <1%
Switzerland 2 <1%
Japan 2 <1%
Turkey 1 <1%
Portugal 1 <1%
Austria 1 <1%
Australia 1 <1%
United Kingdom 1 <1%
Other 5 2%
Unknown 225 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 76 31%
Student > Master 44 18%
Researcher 30 12%
Student > Bachelor 11 4%
Student > Doctoral Student 10 4%
Other 33 13%
Unknown 41 17%
Readers by discipline Count As %
Computer Science 90 37%
Engineering 51 21%
Earth and Planetary Sciences 29 12%
Mathematics 6 2%
Environmental Science 5 2%
Other 19 8%
Unknown 45 18%
Attention Score in Context

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 07 March 2023.
All research outputs
#7,727,332
of 23,495,502 outputs
Outputs from International Journal of Computer Vision
#410
of 1,203 outputs
Outputs of similar age
#52,151
of 156,944 outputs
Outputs of similar age from International Journal of Computer Vision
#3
of 5 outputs
Altmetric has tracked 23,495,502 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,203 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 33rd percentile – i.e., 33% 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 156,944 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% 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. This one has scored higher than 2 of them.