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Explore semantic pixel sets based local patterns with information entropy for face recognition

Overview of attention for article published in EURASIP Journal on Image and Video Processing, May 2014
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
10 Mendeley
Title
Explore semantic pixel sets based local patterns with information entropy for face recognition
Published in
EURASIP Journal on Image and Video Processing, May 2014
DOI 10.1186/1687-5281-2014-26
Authors

Zhenhua Chai, Heydi Mendez-Vazquez, Ran He, Zhenan Sun, Tieniu Tan

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 10%
Unknown 9 90%

Demographic breakdown

Readers by professional status Count As %
Lecturer 2 20%
Student > Ph. D. Student 2 20%
Professor 1 10%
Student > Master 1 10%
Professor > Associate Professor 1 10%
Other 0 0%
Unknown 3 30%
Readers by discipline Count As %
Computer Science 5 50%
Nursing and Health Professions 1 10%
Mathematics 1 10%
Unknown 3 30%
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 October 2021.
All research outputs
#8,534,976
of 25,373,627 outputs
Outputs from EURASIP Journal on Image and Video Processing
#56
of 233 outputs
Outputs of similar age
#80,168
of 241,906 outputs
Outputs of similar age from EURASIP Journal on Image and Video Processing
#2
of 4 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 233 research outputs from this source. They receive a mean Attention Score of 2.9. 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 241,906 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 52% of its contemporaries.
We're also able to compare this research output to 4 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.