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DeConFuse: a deep convolutional transform-based unsupervised fusion framework

Overview of attention for article published in arXiv, May 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

twitter
2 X users
patent
1 patent

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
9 Mendeley
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Title
DeConFuse: a deep convolutional transform-based unsupervised fusion framework
Published in
arXiv, May 2020
DOI 10.1186/s13634-020-00684-5
Authors

Pooja Gupta, Jyoti Maggu, Angshul Majumdar, Emilie Chouzenoux, Giovanni Chierchia

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 22%
Student > Ph. D. Student 2 22%
Student > Doctoral Student 2 22%
Other 1 11%
Lecturer 1 11%
Other 1 11%
Readers by discipline Count As %
Computer Science 3 33%
Economics, Econometrics and Finance 2 22%
Business, Management and Accounting 1 11%
Mathematics 1 11%
Physics and Astronomy 1 11%
Other 0 0%
Unknown 1 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 09 March 2022.
All research outputs
#7,783,733
of 25,387,668 outputs
Outputs from arXiv
#131,874
of 915,148 outputs
Outputs of similar age
#165,627
of 431,497 outputs
Outputs of similar age from arXiv
#4,525
of 25,604 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 915,148 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done well, scoring higher than 85% 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 431,497 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 61% of its contemporaries.
We're also able to compare this research output to 25,604 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.