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X Demographics
Mendeley readers
Chapter title |
Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation
|
---|---|
Chapter number | 34 |
Book title |
Medical Image Computing and Computer Assisted Intervention – MICCAI 2019
|
Published by |
Springer, Cham, October 2019
|
DOI | 10.1007/978-3-030-32245-8_34 |
Book ISBNs |
978-3-03-032244-1, 978-3-03-032245-8
|
Authors |
Utku Ozbulak, Arnout Van Messem, Wesley De Neve, Ozbulak, Utku, Van Messem, Arnout, De Neve, Wesley |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 62 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 19 | 31% |
Researcher | 5 | 8% |
Student > Master | 5 | 8% |
Professor > Associate Professor | 3 | 5% |
Student > Bachelor | 2 | 3% |
Other | 8 | 13% |
Unknown | 20 | 32% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 23 | 37% |
Engineering | 8 | 13% |
Biochemistry, Genetics and Molecular Biology | 2 | 3% |
Sports and Recreations | 2 | 3% |
Mathematics | 1 | 2% |
Other | 4 | 6% |
Unknown | 22 | 35% |