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The application of support vector machine classification to detect cell nuclei for automated microscopy

Overview of attention for article published in Machine Vision and Applications, June 2010
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Mentioned by

wikipedia
4 Wikipedia pages

Citations

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34 Dimensions

Readers on

mendeley
103 Mendeley
citeulike
1 CiteULike
Title
The application of support vector machine classification to detect cell nuclei for automated microscopy
Published in
Machine Vision and Applications, June 2010
DOI 10.1007/s00138-010-0275-y
Authors

Ji Wan Han, Toby P. Breckon, David A. Randell, Gabriel Landini

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
Netherlands 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
China 1 <1%
Unknown 97 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 22%
Student > Bachelor 14 14%
Researcher 13 13%
Student > Master 13 13%
Student > Doctoral Student 6 6%
Other 12 12%
Unknown 22 21%
Readers by discipline Count As %
Engineering 23 22%
Agricultural and Biological Sciences 16 16%
Computer Science 14 14%
Medicine and Dentistry 6 6%
Physics and Astronomy 4 4%
Other 15 15%
Unknown 25 24%
Attention Score in Context

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 22 March 2023.
All research outputs
#7,845,540
of 23,794,258 outputs
Outputs from Machine Vision and Applications
#162
of 551 outputs
Outputs of similar age
#35,317
of 98,092 outputs
Outputs of similar age from Machine Vision and Applications
#3
of 5 outputs
Altmetric has tracked 23,794,258 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 551 research outputs from this source. They receive a mean Attention Score of 3.7. This one is in the 40th percentile – i.e., 40% 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 98,092 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.