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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A Retinotopic Spiking Neural Network System for Accurate Recognition of Moving Objects Using NeuCube and Dynamic Vision Sensors
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, June 2018
|
| DOI | 10.3389/fncom.2018.00042 |
| Pubmed ID | |
| Authors |
Lukas Paulun, Anne Wendt, Nikola Kasabov |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 1 | 17% |
| Switzerland | 1 | 17% |
| United States | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 69 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 20 | 29% |
| Student > Master | 11 | 16% |
| Researcher | 6 | 9% |
| Student > Doctoral Student | 4 | 6% |
| Student > Bachelor | 4 | 6% |
| Other | 4 | 6% |
| Unknown | 20 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 18 | 26% |
| Engineering | 15 | 22% |
| Neuroscience | 6 | 9% |
| Biochemistry, Genetics and Molecular Biology | 1 | 1% |
| Social Sciences | 1 | 1% |
| Other | 3 | 4% |
| Unknown | 25 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 16 April 2024.
All research outputs
#4,341,004
of 25,722,279 outputs
Outputs from Frontiers in Computational Neuroscience
#194
of 1,475 outputs
Outputs of similar age
#77,360
of 342,552 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#8
of 31 outputs
Altmetric has tracked 25,722,279 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,475 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has done well, scoring higher than 86% 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 342,552 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 31 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 74% of its contemporaries.