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Mendeley readers
Attention Score in Context
Chapter title |
Reading Ancient Coins: Automatically Identifying Denarii Using Obverse Legend Seeded Retrieval
|
---|---|
Chapter number | 23 |
Book title |
Computer Vision – ECCV 2012
|
Published in |
Lecture notes in computer science, January 2012
|
DOI | 10.1007/978-3-642-33765-9_23 |
Book ISBNs |
978-3-64-233764-2, 978-3-64-233765-9
|
Authors |
Ognjen Arandjelović, Arandjelović, Ognjen |
Editors |
Andrew Fitzgibbon, Svetlana Lazebnik, Pietro Perona, Yoichi Sato, Cordelia Schmid |
Mendeley readers
The data shown below were compiled from readership statistics for 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 8% |
Unknown | 12 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Professor > Associate Professor | 4 | 31% |
Researcher | 3 | 23% |
Student > Bachelor | 2 | 15% |
Student > Master | 2 | 15% |
Unknown | 2 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 7 | 54% |
Engineering | 3 | 23% |
Unknown | 3 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 18 March 2019.
All research outputs
#4,193,400
of 22,890,496 outputs
Outputs from Lecture notes in computer science
#989
of 8,127 outputs
Outputs of similar age
#35,645
of 244,740 outputs
Outputs of similar age from Lecture notes in computer science
#64
of 490 outputs
Altmetric has tracked 22,890,496 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,127 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done well, scoring higher than 82% 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 244,740 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 84% of its contemporaries.
We're also able to compare this research output to 490 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.