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A Two-To-One Deep Learning General Framework for Image Fusion

Overview of attention for article published in Frontiers in Bioengineering and Biotechnology, July 2022
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
5 Mendeley
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Title
A Two-To-One Deep Learning General Framework for Image Fusion
Published in
Frontiers in Bioengineering and Biotechnology, July 2022
DOI 10.3389/fbioe.2022.923364
Pubmed ID
Authors

Pan Zhu, Wanqi Ouyang, Yongxing Guo, Xinglin Zhou

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 20%
Lecturer 1 20%
Unknown 3 60%
Readers by discipline Count As %
Unspecified 1 20%
Computer Science 1 20%
Agricultural and Biological Sciences 1 20%
Unknown 2 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 01 August 2022.
All research outputs
#17,918,662
of 23,006,268 outputs
Outputs from Frontiers in Bioengineering and Biotechnology
#2,931
of 6,714 outputs
Outputs of similar age
#286,323
of 434,636 outputs
Outputs of similar age from Frontiers in Bioengineering and Biotechnology
#228
of 641 outputs
Altmetric has tracked 23,006,268 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,714 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 434,636 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 641 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 54% of its contemporaries.