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Semantic Modeling of Natural Scenes for Content-Based Image Retrieval

Overview of attention for article published in International Journal of Computer Vision, July 2006
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Mentioned by

patent
2 patents

Readers on

mendeley
187 Mendeley
citeulike
3 CiteULike
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Title
Semantic Modeling of Natural Scenes for Content-Based Image Retrieval
Published in
International Journal of Computer Vision, July 2006
DOI 10.1007/s11263-006-8614-1
Authors

Julia Vogel, Bernt Schiele

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 187 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 5%
Germany 4 2%
Spain 3 2%
Netherlands 2 1%
Russia 2 1%
China 2 1%
Finland 2 1%
Italy 1 <1%
Austria 1 <1%
Other 8 4%
Unknown 153 82%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 66 35%
Student > Master 36 19%
Researcher 29 16%
Student > Doctoral Student 11 6%
Student > Bachelor 9 5%
Other 27 14%
Unknown 9 5%
Readers by discipline Count As %
Computer Science 100 53%
Engineering 33 18%
Psychology 9 5%
Earth and Planetary Sciences 5 3%
Agricultural and Biological Sciences 4 2%
Other 15 8%
Unknown 21 11%
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 21 May 2019.
All research outputs
#7,550,598
of 23,035,022 outputs
Outputs from International Journal of Computer Vision
#399
of 1,163 outputs
Outputs of similar age
#22,904
of 65,853 outputs
Outputs of similar age from International Journal of Computer Vision
#4
of 10 outputs
Altmetric has tracked 23,035,022 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 1,163 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 31st percentile – i.e., 31% 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 65,853 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.