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Deep Features Extraction for Robust Fingerprint Spoofing Attack Detection Cover

References

  1. [1] A. Jain, A. Ross and K. Nandakumar, Introduction to Biometrics, Springer, 2011.10.1007/978-0-387-77326-1
  2. [2] A Biniaz and A. Abbasi, Segmentation and edge detection based on modified ant colony optimization for iris image processing, Journal of Artificial Intelligence and Soft Computing Research (JAISCR), vol. 3, no. 2, 2013, pp. 133-141.10.2478/jaiscr-2014-0010
  3. [3] D. Menotti, G. Chiachia, A. Pinto, W. Schwartz, H. Pedrini, A. Falcao and A. Rocha, Deep representations for iris, face, and fingerprint spoofing attack detection, IEEE Transactions on Information Forensics and Security, vol. 10, no. 4, 2015, pp. 864-879.10.1109/TIFS.2015.2398817
  4. [4] L. Ghiani, V. Mura, S. Tocco, G. Marcialis, F. Roli, D. Yambay and S. Schuckers, LivDet 2013 fingerprint liveness detection competition, In: Proceedings of International Conference on Biometrics, 2013, pp. 1-6.10.1109/ICB.2013.6613027
  5. [5] G. Souza, D. Santos, R. Pires, A. Marana, J. Papa, Deep Boltzmann Machines for robust fingerprint spoofing attack detection, In: Proceedings of International Joint Conference on Neural Networks, 2017, pp. 1863-1870.10.1109/IJCNN.2017.7966077
  6. [6] R. Salakhutdinov and G. Hinton, Deep Boltzmann Machines, Technical Report, University of Toronto, 2009.
  7. [7] G. Hinton, Training products of experts by minimizing Contrastive Divergence, Neural Computation, vol. 14, no. 2, 2002, pp.1771-1800.10.1162/089976602760128018
  8. [8] G. Hinton, Neural networks: tricks of the trade, Springer, Berlin, 2012.
  9. [9] N. Ratha, J. Connel and R. Bolle, An analysis of minutiae matching strength, In: Proceedings of International Conference on Audio- and Video-Based Biometric Person Authentication, 2001, pp. 223-228.10.1007/3-540-45344-X_32
  10. [10] J. Galbally, J. Fierrez and J. Garcia, Vulnerabilities in biometric systems: attacks and recent advances in liveness detection, Database, vol. 1, no. 3, 2007, pp. 1-8.
  11. [11] K. Patel, H. Han and A. Jain, Cross-database face antispoofing with robust feature representation, In: Proceedings of Chinese Conference on Biometric Recognition, 2016, pp. 611-619.10.1007/978-3-319-46654-5_67
  12. [12] V. Nair and G. Hinton, Implicit mixtures of Restricted Boltzmann Machines, Advances in Neural Information Processing Systems, vol. 21, 2009, pp. 1145-1152.
  13. [13] D. MacKays, Information theory, inference and learning algorithms, Cambridge University Press, 2003.
  14. [14] R. Salakhutdinov and H. Larochelle, Efficient learning of Deep Boltzmann Machines, Artificial Intelligence and Statistics, 2010, pp. 693-700.
  15. [15] S. Kullback, Probability densities with given marginals, Annals of Mathematical Statistics, vol. 39, no. 4, 1968, pp. 1236-1243.10.1214/aoms/1177698249
  16. [16] I. Navon and D. Legler, Conjugate-gradient methods for large-scale minimization in Meteorology, Monthly Weather Review, American Meteorological Society, vol. 115, 1987, pp. 1479-1502.10.1175/1520-0493(1987)115<;1479:CGMFLS>2.0.CO;2
  17. [17] Y. LeCun, L. Bottou, G. Orr and K. Müller, Efficient Backprop., Springer-Verlag, United Kingdom, 1998.10.1007/3-540-49430-8_2
  18. [18] C. Cortes and V. Vapnik, Support-vector networks, Machine Learning, vol. 20, no. 3, 1995, pp. 273-297.10.1007/BF00994018
  19. [19] H. Hotelling, Analysis of a complex of statistical variables into principal components, Journal of Educational Psychology, vol. 24, 1933, pp. 417-441.10.1037/h0071325
Language: English
Page range: 41 - 49
Submitted on: Dec 13, 2017
Accepted on: Dec 20, 2017
Published on: Aug 20, 2018
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2018 Gustavo Botelho de Souza, Daniel Felipe da Silva Santos, Rafael Gonçalves Pires, Aparecido Nilceu Marana, João Paulo Papa, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.