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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Event-driven visual attention for the humanoid robot iCub
|
|---|---|
| Published in |
Frontiers in Neuroscience, January 2013
|
| DOI | 10.3389/fnins.2013.00234 |
| Pubmed ID | |
| Authors |
Francesco Rea, Giorgio Metta, Chiara Bartolozzi |
| Abstract |
Fast reaction to sudden and potentially interesting stimuli is a crucial feature for safe and reliable interaction with the environment. Here we present a biologically inspired attention system developed for the humanoid robot iCub. It is based on input from unconventional event-driven vision sensors and an efficient computational method. The resulting system shows low-latency and fast determination of the location of the focus of attention. The performance is benchmarked against an instance of the state of the art in robotics artificial attention system used in robotics. Results show that the proposed system is two orders of magnitude faster that the benchmark in selecting a new stimulus to attend. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| Portugal | 2 | 3% |
| France | 1 | 2% |
| Unknown | 60 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 20% |
| Student > Master | 10 | 15% |
| Researcher | 10 | 15% |
| Student > Doctoral Student | 4 | 6% |
| Student > Bachelor | 3 | 5% |
| Other | 10 | 15% |
| Unknown | 15 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 16 | 25% |
| Computer Science | 11 | 17% |
| Neuroscience | 4 | 6% |
| Physics and Astronomy | 3 | 5% |
| Psychology | 3 | 5% |
| Other | 9 | 14% |
| Unknown | 19 | 29% |
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 14 December 2013.
All research outputs
#19,944,091
of 25,373,627 outputs
Outputs from Frontiers in Neuroscience
#8,668
of 11,538 outputs
Outputs of similar age
#221,299
of 288,991 outputs
Outputs of similar age from Frontiers in Neuroscience
#169
of 246 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,538 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one is in the 18th percentile – i.e., 18% 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 288,991 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 246 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.