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Eyelid and Pupil Landmark Detection and Blink Estimation Based on Deformable Shape Models for Near-Field Infrared Video

Overview of attention for article published in Frontiers in ICT, October 2019
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About this Attention Score

  • Among the highest-scoring outputs from this source (#49 of 143)
  • Above-average Attention Score compared to outputs of the same age (56th percentile)

Mentioned by

patent
1 patent

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
13 Mendeley
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Title
Eyelid and Pupil Landmark Detection and Blink Estimation Based on Deformable Shape Models for Near-Field Infrared Video
Published in
Frontiers in ICT, October 2019
DOI 10.3389/fict.2019.00018
Authors

Siyuan Chen, Julien Epps

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 23%
Student > Ph. D. Student 2 15%
Student > Master 2 15%
Student > Doctoral Student 1 8%
Lecturer 1 8%
Other 0 0%
Unknown 4 31%
Readers by discipline Count As %
Computer Science 4 31%
Engineering 4 31%
Unknown 5 38%
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 10 November 2022.
All research outputs
#7,564,023
of 23,072,295 outputs
Outputs from Frontiers in ICT
#49
of 143 outputs
Outputs of similar age
#137,879
of 353,988 outputs
Outputs of similar age from Frontiers in ICT
#1
of 2 outputs
Altmetric has tracked 23,072,295 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 143 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has gotten more attention than average, scoring higher than 65% 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 353,988 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 56% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them