Önceden Eğitilmiş Çeşitli Derin Sinir Ağları Kullanarak Parmak İzi Örüntü Sınıflandırma

Author:

CIMTAY Yucel,ALKAN Bensu,DEMİREL Berkan

Publisher

European Journal of Science and Technology

Reference18 articles.

1. [1] I. Shrestha and B. K. Malla, “Study of Fingerprint Patterns in Population of a Community”,J Nepal Med Assoc, vol. 57, no. 219, Oct. 2019.

2. [2] J. Y. Kang, J. S. Lee, J. H. Lee, S. M. Kong, D. H. Kim, and S. B. Lee, “A study on the dynamic binary fingerprint recognition method using artificial intelligence,” Journal of Korean Institute of Intelligent Systems, vol. 13, no. 1, pp. 57-62, 2003. https://doi.org/10.5391/JKIIS.2003.13.1.057

3. [3] W. J. Kim, C. G. Lee, Y. T. Kim, and S. B. Lee, “Implementation of embedded system and finger print identification using ART2,” Proceedings of KIFS Spring Conference, vol. 16, no. 1, pp. 90-93, 2006.

4. [4] H. W. Jung and J. H. Lee, “Various quality fingerprint classification using the optimal stochastic models,” Journal of the Korea Society for Simulation, vol. 19, no. 1, pp. 143-151, 2010.

5. [5] A. Krizhevsky, I. Sutskever, and G. E. Hinton, “ImageNet classification with deep convolutional neural networks,” in Proceeding of Neural Information Processing Systems Conference and Workshop, Lake Tahoe, NV, 2012, pp. 1097-1105

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