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Mendeley readers
Chapter title |
Coronavirus (COVID-19) Classification Using Deep Features Fusion and Ranking Technique
|
---|---|
Chapter number | 17 |
Book title |
Big Data Analytics and Artificial Intelligence Against COVID-19: Innovation Vision and Approach
|
Published by |
Springer, Cham, October 2020
|
DOI | 10.1007/978-3-030-55258-9_17 |
Book ISBNs |
978-3-03-055257-2, 978-3-03-055258-9
|
Authors |
Umut Özkaya, Şaban Öztürk, Mucahid Barstugan, Özkaya, Umut, Öztürk, Şaban, Barstugan, Mucahid |
Mendeley readers
The data shown below were compiled from readership statistics for 146 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 146 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 18 | 12% |
Researcher | 14 | 10% |
Student > Bachelor | 14 | 10% |
Student > Ph. D. Student | 10 | 7% |
Student > Doctoral Student | 6 | 4% |
Other | 28 | 19% |
Unknown | 56 | 38% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 49 | 34% |
Engineering | 13 | 9% |
Medicine and Dentistry | 4 | 3% |
Social Sciences | 3 | 2% |
Business, Management and Accounting | 2 | 1% |
Other | 12 | 8% |
Unknown | 63 | 43% |