The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Timeline
X Demographics
Mendeley readers
Attention Score in Context
Title |
Salt and Pepper Noise Removal Method Based on the Edge-Adaptive Total Variation Model
|
---|---|
Published in |
Frontiers in Applied Mathematics and Statistics, June 2022
|
DOI | 10.3389/fams.2022.918357 |
Authors |
Yunyun Jiang, Hefei Wang, Yi Cai, Bo Fu |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 14 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 1 | 7% |
Student > Ph. D. Student | 1 | 7% |
Student > Master | 1 | 7% |
Researcher | 1 | 7% |
Professor > Associate Professor | 1 | 7% |
Other | 1 | 7% |
Unknown | 8 | 57% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 3 | 21% |
Engineering | 2 | 14% |
Decision Sciences | 1 | 7% |
Environmental Science | 1 | 7% |
Unknown | 7 | 50% |
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 15 June 2022.
All research outputs
#20,165,369
of 22,675,759 outputs
Outputs from Frontiers in Applied Mathematics and Statistics
#262
of 337 outputs
Outputs of similar age
#352,444
of 437,297 outputs
Outputs of similar age from Frontiers in Applied Mathematics and Statistics
#4
of 10 outputs
Altmetric has tracked 22,675,759 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 337 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 1st percentile – i.e., 1% 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 437,297 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 6 of them.