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Mendeley readers
Attention Score in Context
Chapter title |
The Importance of Skip Connections in Biomedical Image Segmentation
|
---|---|
Chapter number | 19 |
Book title |
Deep Learning and Data Labeling for Medical Applications
|
Published in |
Lecture notes in computer science, September 2016
|
DOI | 10.1007/978-3-319-46976-8_19 |
Book ISBNs |
978-3-31-946975-1, 978-3-31-946976-8
|
Authors |
Michal Drozdzal, Eugene Vorontsov, Gabriel Chartrand, Samuel Kadoury, Chris Pal, Drozdzal, Michal, Vorontsov, Eugene, Chartrand, Gabriel, Kadoury, Samuel, Pal, Chris |
Mendeley readers
The data shown below were compiled from readership statistics for 763 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 1 | <1% |
Brazil | 1 | <1% |
Unknown | 761 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 166 | 22% |
Student > Ph. D. Student | 153 | 20% |
Researcher | 82 | 11% |
Student > Bachelor | 59 | 8% |
Student > Doctoral Student | 32 | 4% |
Other | 75 | 10% |
Unknown | 196 | 26% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 267 | 35% |
Engineering | 156 | 20% |
Medicine and Dentistry | 18 | 2% |
Physics and Astronomy | 16 | 2% |
Agricultural and Biological Sciences | 14 | 2% |
Other | 65 | 9% |
Unknown | 227 | 30% |
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 13 February 2024.
All research outputs
#7,954,424
of 23,943,619 outputs
Outputs from Lecture notes in computer science
#2,501
of 8,168 outputs
Outputs of similar age
#117,785
of 326,821 outputs
Outputs of similar age from Lecture notes in computer science
#171
of 554 outputs
Altmetric has tracked 23,943,619 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 8,168 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 54% 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 326,821 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 50% of its contemporaries.
We're also able to compare this research output to 554 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.