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Mendeley readers
Chapter title |
Diagnosis of Bearing Faults in Electrical Machines Using Long Short-Term Memory (LSTM)
|
---|---|
Chapter number | 4 |
Book title |
Deep Learning Applications, Volume 2
|
Published by |
Springer, Singapore, January 2021
|
DOI | 10.1007/978-981-15-6759-9_4 |
Book ISBNs |
978-9-81-156758-2, 978-9-81-156759-9
|
Authors |
Russell Sabir, Daniele Rosato, Sven Hartmann, Clemens Gühmann, Sabir, Russell, Rosato, Daniele, Hartmann, Sven, Gühmann, Clemens |
Mendeley readers
The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 15 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Doctoral Student | 4 | 27% |
Professor > Associate Professor | 2 | 13% |
Lecturer > Senior Lecturer | 1 | 7% |
Student > Bachelor | 1 | 7% |
Lecturer | 1 | 7% |
Other | 2 | 13% |
Unknown | 4 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Engineering | 4 | 27% |
Computer Science | 3 | 20% |
Chemical Engineering | 1 | 7% |
Nursing and Health Professions | 1 | 7% |
Materials Science | 1 | 7% |
Other | 1 | 7% |
Unknown | 4 | 27% |