↓ Skip to main content

A Multiphase Image Segmentation Based on Fuzzy Membership Functions and L1-Norm Fidelity

Overview of attention for article published in Journal of Scientific Computing, February 2016
Altmetric Badge

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 (51st percentile)

Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
5 Mendeley
Title
A Multiphase Image Segmentation Based on Fuzzy Membership Functions and L1-Norm Fidelity
Published in
Journal of Scientific Computing, February 2016
DOI 10.1007/s10915-016-0183-z
Authors

Fang Li, Stanley Osher, Jing Qin, Ming Yan

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

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 %
United States 1 20%
Unknown 4 80%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 60%
Professor 1 20%
Unspecified 1 20%
Readers by discipline Count As %
Computer Science 2 40%
Mathematics 1 20%
Unspecified 1 20%
Engineering 1 20%

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 08 August 2016.
All research outputs
#9,481,729
of 12,371,167 outputs
Outputs from Journal of Scientific Computing
#266,338
of 579,193 outputs
Outputs of similar age
#144,851
of 226,295 outputs
Outputs of similar age from Journal of Scientific Computing
#6,916
of 20,402 outputs
Altmetric has tracked 12,371,167 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 579,193 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 39th percentile – i.e., 39% 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 226,295 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 20,402 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 51% of its contemporaries.