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Mendeley readers
Chapter title |
Abstract: nnU-Net: Self-adapting Framework for U-Net-Based Medical Image Segmentation
|
---|---|
Chapter number | 7 |
Book title |
Bildverarbeitung für die Medizin 2019
|
Published by |
Springer Vieweg, Wiesbaden, January 2019
|
DOI | 10.1007/978-3-658-25326-4_7 |
Book ISBNs |
978-3-65-825325-7, 978-3-65-825326-4
|
Authors |
Fabian Isensee, Jens Petersen, Andre Klein, David Zimmerer, Paul F. Jaeger, Simon Kohl, Jakob Wasserthal, Gregor Koehler, Tobias Norajitra, Sebastian Wirkert, Klaus H. Maier-Hein, Isensee, Fabian, Petersen, Jens, Klein, Andre, Zimmerer, David, Jaeger, Paul F., Kohl, Simon, Wasserthal, Jakob, Koehler, Gregor, Norajitra, Tobias, Wirkert, Sebastian, Maier-Hein, Klaus H. |
Mendeley readers
The data shown below were compiled from readership statistics for 938 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 938 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 154 | 16% |
Student > Ph. D. Student | 146 | 16% |
Researcher | 95 | 10% |
Student > Bachelor | 73 | 8% |
Student > Postgraduate | 28 | 3% |
Other | 66 | 7% |
Unknown | 376 | 40% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 255 | 27% |
Engineering | 139 | 15% |
Medicine and Dentistry | 29 | 3% |
Physics and Astronomy | 22 | 2% |
Neuroscience | 15 | 2% |
Other | 51 | 5% |
Unknown | 427 | 46% |