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Mendeley readers
Chapter title |
Improving Semantic Embedding Consistency by Metric Learning for Zero-Shot Classiffication
|
---|---|
Chapter number | 44 |
Book title |
Computer Vision – ECCV 2016
|
Published by |
Springer International Publishing, January 2016
|
DOI | 10.1007/978-3-319-46454-1_44 |
Book ISBNs |
978-3-31-946453-4, 978-3-31-946454-1
|
Authors |
Maxime Bucher, Stéphane Herbin, Frédéric Jurie, Bucher, Maxime, Herbin, Stéphane, Jurie, Frédéric |
Editors |
Bastian Leibe, Jiri Matas, Nicu Sebe, Max Welling |
Mendeley readers
The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | <1% |
Argentina | 1 | <1% |
Unknown | 119 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 39 | 32% |
Student > Master | 19 | 16% |
Researcher | 15 | 12% |
Student > Bachelor | 5 | 4% |
Student > Doctoral Student | 4 | 3% |
Other | 12 | 10% |
Unknown | 27 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 75 | 62% |
Engineering | 9 | 7% |
Biochemistry, Genetics and Molecular Biology | 2 | 2% |
Physics and Astronomy | 2 | 2% |
Social Sciences | 1 | <1% |
Other | 1 | <1% |
Unknown | 31 | 26% |