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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Improving accuracy and speeding up Document Image Classification through
parallel systems
|
---|---|
Chapter number | 29 |
Book title |
Computational Science – ICCS 2020
|
Published in |
arXiv, June 2020
|
DOI | 10.1007/978-3-030-50417-5_29 |
Book ISBNs |
978-3-03-050416-8, 978-3-03-050417-5
|
Authors |
Javier Ferrando, Juan Luis Dominguez, Jordi Torres, Raul Garcia, David Garcia, Daniel Garrido, Jordi Cortada, Mateo Valero, Juan Luis Domínguez, Raúl García, David García, Ferrando Monsonis, Javier, Domínguez, Juan Luis, Torres Viñals, Jordi, García Fuentes, Raul, García Doménech, David, Garrido Miñambres, Daniel, Cortada, Jordi, Valero Cortés, Mateo, Ferrando, Javier, Torres, Jordi, García, Raúl, García, David, Garrido, Daniel, Valero, Mateo |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | 14% |
Japan | 1 | 14% |
Unknown | 5 | 71% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 32 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 6 | 19% |
Researcher | 4 | 13% |
Student > Bachelor | 2 | 6% |
Other | 2 | 6% |
Student > Ph. D. Student | 2 | 6% |
Other | 1 | 3% |
Unknown | 15 | 47% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 12 | 38% |
Engineering | 3 | 9% |
Decision Sciences | 1 | 3% |
Business, Management and Accounting | 1 | 3% |
Unknown | 15 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 29 June 2020.
All research outputs
#13,802,202
of 24,093,053 outputs
Outputs from arXiv
#206,161
of 1,020,419 outputs
Outputs of similar age
#191,567
of 402,051 outputs
Outputs of similar age from arXiv
#7,589
of 34,620 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,020,419 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 78% 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 402,051 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 34,620 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.