On the use of convolutional neural networks for robust classification of multiple fingerprint captures-Reference-Cited by-同舟云学术

On the use of convolutional neural networks for robust classification of multiple fingerprint captures

Published:2017-11-14 Issue:1 Volume:33 Page:213-230
ISSN:0884-8173
Container-title:International Journal of Intelligent Systems
language:en
Short-container-title:Int. J. Intell. Syst.

Author:

Peralta Daniel¹²,Triguero Isaac³,García Salvador⁴,Saeys Yvan¹²,Benitez Jose M.⁴,Herrera Francisco⁴⁵

Affiliation:

1. Department of Applied Mathematics, Computer Science and Statistics; Ghent University; Ghent Belgium

2. Data Mining and Modelling for Biomedicine group; VIB Center for Inflammation Research; Ghent Belgium

3. School of Computer Science; University of Nottingham; Jubilee Campus Nottingham UK

4. Department of Computer Science and Artificial Intelligence of the University of Granada; Granada Spain

5. Faculty of Computing and Information Technology; King Abdulaziz University; Jeddah Saudi Arabia

Funder

Ministerio de Ciencia y Tecnología

Fundación BBVA

Publisher

Wiley

Subject

Artificial Intelligence,Human-Computer Interaction,Theoretical Computer Science,Software

Reference68 articles.

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2. Ratha N Bolle R Pandit V Vaish V Robust fingerprint authentication using local structural similarity Proceedings of the Fifth IEEE Workshop on Applications of Computer Vision Washington, DC IEEE Computer Society 2000 29 34

3. Jiang X Yau WY Fingerprint minutiae matching based on the local and global structures Proceedings of the 15th International Conference on Pattern Recognition Piscataway, New Jersey, USA IEEE 2000 1038 1041

4. Minutia cylinder-code: a new representation and matching technique for fingerprint recognition;Cappelli;IEEE Trans Pattern Anal,2010

5. A survey on fingerprint minutiae-based local matching for verification and identification: taxonomy and experimental evaluation;Peralta;Inform Sci,2015

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