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Mendeley readers
Chapter title |
Quantitative Comparison of Monte-Carlo Dropout Uncertainty Measures for Multi-class Segmentation
|
---|---|
Chapter number | 4 |
Book title |
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis
|
Published by |
Springer, Cham, October 2020
|
DOI | 10.1007/978-3-030-60365-6_4 |
Book ISBNs |
978-3-03-060364-9, 978-3-03-060365-6
|
Authors |
Robin Camarasa, Daniel Bos, Jeroen Hendrikse, Paul Nederkoorn, Eline Kooi, Aad van der Lugt, Marleen de Bruijne |
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 % |
---|---|---|
Unknown | 13 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 4 | 31% |
Professor | 2 | 15% |
Researcher | 2 | 15% |
Student > Master | 1 | 8% |
Unknown | 4 | 31% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 4 | 31% |
Engineering | 2 | 15% |
Biochemistry, Genetics and Molecular Biology | 1 | 8% |
Medicine and Dentistry | 1 | 8% |
Physics and Astronomy | 1 | 8% |
Other | 0 | 0% |
Unknown | 4 | 31% |