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A Total Variation Regularization Based Super-Resolution Reconstruction Algorithm for Digital Video

Overview of attention for article published in EURASIP Journal on Advances in Signal Processing, June 2007
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About this Attention Score

  • One of the highest-scoring outputs from this source (#2 of 119)
  • Good Attention Score compared to outputs of the same age (73rd percentile)

Mentioned by

wikipedia
1 Wikipedia page

Citations

dimensions_citation
154 Dimensions

Readers on

mendeley
53 Mendeley
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Title
A Total Variation Regularization Based Super-Resolution Reconstruction Algorithm for Digital Video
Published in
EURASIP Journal on Advances in Signal Processing, June 2007
DOI 10.1155/2007/74585
Authors

Michael K. Ng, Huanfeng Shen, Edmund Y. Lam, Liangpei Zhang

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
Sweden 1 2%
Brazil 1 2%
Unknown 49 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 34%
Researcher 7 13%
Student > Doctoral Student 7 13%
Student > Master 4 8%
Student > Bachelor 3 6%
Other 9 17%
Unknown 5 9%
Readers by discipline Count As %
Engineering 22 42%
Computer Science 18 34%
Earth and Planetary Sciences 2 4%
Biochemistry, Genetics and Molecular Biology 1 2%
Mathematics 1 2%
Other 3 6%
Unknown 6 11%

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 12 March 2014.
All research outputs
#817,841
of 3,626,860 outputs
Outputs from EURASIP Journal on Advances in Signal Processing
#2
of 119 outputs
Outputs of similar age
#24,157
of 93,566 outputs
Outputs of similar age from EURASIP Journal on Advances in Signal Processing
#1
of 1 outputs
Altmetric has tracked 3,626,860 research outputs across all sources so far. This one has received more attention than most of these and is in the 63rd percentile.
So far Altmetric has tracked 119 research outputs from this source. They receive a mean Attention Score of 0.7. This one has done particularly well, scoring higher than 91% 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 93,566 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 73% of its contemporaries.
We're also able to compare this research output to 1 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