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Mendeley readers
Title |
On the multi-agent learning neural and Bayesian methods in skin detector and pornography classifier: An automated anti-pornography system
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Published in |
Neurocomputing, May 2014
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DOI | 10.1016/j.neucom.2013.10.003 |
Authors |
A.A. Zaidan, N.N. Ahmad, H. Abdul Karim, M. Larbani, B.B. Zaidan, A. Sali |
Mendeley readers
The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Malaysia | 2 | 4% |
Unknown | 51 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 14 | 26% |
Student > Master | 11 | 21% |
Researcher | 6 | 11% |
Professor > Associate Professor | 5 | 9% |
Student > Doctoral Student | 4 | 8% |
Other | 7 | 13% |
Unknown | 6 | 11% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 25 | 47% |
Engineering | 9 | 17% |
Mathematics | 3 | 6% |
Materials Science | 3 | 6% |
Business, Management and Accounting | 2 | 4% |
Other | 3 | 6% |
Unknown | 8 | 15% |