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Attention Score in Context
Chapter title |
Text Localization in Historical Document Images with Local Binary Patterns and Variance Models
|
---|---|
Chapter number | 69 |
Book title |
Pattern Recognition and Machine Intelligence
|
Published in |
Lecture notes in computer science, December 2013
|
DOI | 10.1007/978-3-642-45062-4_69 |
Book ISBNs |
978-3-64-245061-7, 978-3-64-245062-4
|
Authors |
Tapan Kumar Bhowmik, Manika Kar, Bhowmik, Tapan Kumar, Kar, Manika |
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 10 January 2014.
All research outputs
#20,216,580
of 22,739,983 outputs
Outputs from Lecture notes in computer science
#6,983
of 8,126 outputs
Outputs of similar age
#266,990
of 306,808 outputs
Outputs of similar age from Lecture notes in computer science
#249
of 293 outputs
Altmetric has tracked 22,739,983 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,126 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 1st percentile – i.e., 1% 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 306,808 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 293 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.