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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Unsupervised Few-Shot Feature Learning via Self-Supervised Training
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, October 2020
|
| DOI | 10.3389/fncom.2020.00083 |
| Pubmed ID | |
| Authors |
Zilong Ji, Xiaolong Zou, Tiejun Huang, Si Wu |
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.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 72 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 22% |
| Student > Master | 13 | 18% |
| Researcher | 5 | 7% |
| Student > Bachelor | 4 | 6% |
| Student > Postgraduate | 4 | 6% |
| Other | 7 | 10% |
| Unknown | 23 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 31 | 43% |
| Engineering | 6 | 8% |
| Environmental Science | 1 | 1% |
| Mathematics | 1 | 1% |
| Physics and Astronomy | 1 | 1% |
| Other | 3 | 4% |
| Unknown | 29 | 40% |
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 25 October 2020.
All research outputs
#18,097,821
of 23,253,955 outputs
Outputs from Frontiers in Computational Neuroscience
#974
of 1,368 outputs
Outputs of similar age
#295,108
of 415,914 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#21
of 27 outputs
Altmetric has tracked 23,253,955 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 1,368 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 22nd percentile – i.e., 22% 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 415,914 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 11th percentile – i.e., 11% of its contemporaries scored the same or lower than it.