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Deep feature representation and multiple metric ensembles for person re-identification in security surveillance system

Overview of attention for article published in Multimedia Tools and Applications, April 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

blogs
1 blog

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
18 Mendeley
Title
Deep feature representation and multiple metric ensembles for person re-identification in security surveillance system
Published in
Multimedia Tools and Applications, April 2017
DOI 10.1007/s11042-017-4649-2
Authors

Meibin Qi, Jingxian Han, Jianguo Jiang, Hao Liu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 28%
Student > Master 5 28%
Student > Postgraduate 2 11%
Student > Doctoral Student 1 6%
Other 1 6%
Other 1 6%
Unknown 3 17%
Readers by discipline Count As %
Computer Science 7 39%
Engineering 5 28%
Unspecified 1 6%
Social Sciences 1 6%
Earth and Planetary Sciences 1 6%
Other 0 0%
Unknown 3 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 24 June 2019.
All research outputs
#6,128,890
of 23,906,448 outputs
Outputs from Multimedia Tools and Applications
#249
of 4,321 outputs
Outputs of similar age
#92,793
of 312,758 outputs
Outputs of similar age from Multimedia Tools and Applications
#12
of 38 outputs
Altmetric has tracked 23,906,448 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 4,321 research outputs from this source. They receive a mean Attention Score of 1.3. This one has done particularly well, scoring higher than 94% 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 312,758 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 69% of its contemporaries.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.