An effective deep learning features based integrated framework for iris detection and recognition
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Computer Science
Link
https://link.springer.com/content/pdf/10.1007/s12652-020-02172-y.pdf
Reference18 articles.
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2. Bastys A, Kranauskas J, Krüger V (2011) Iris recognition by fusing different representations of multi-scale Taylor expansion. Comput Vis Image Understand 115(6):804–816. https://doi.org/10.1016/j.cviu.2011.02.004
3. Bengio Y, Courville A, Vincent P (2013) Representation learning: a review and new perspectives. IEEE Trans Pattern Anal Mach Intell 35(8):1798–1828. https://doi.org/10.1109/TPAMI.2013.50
4. Bowyer KW, Hollingsworth K, Flynn PJ (2008) Image understanding for iris biometrics: a survey. Comput Vis Image Understand 110(2):281–307. https://doi.org/10.1016/j.cviu.2007.08.005
5. Bowyer KW, Hollingsworth K, Flynn PJ (2013) A survey of iris biometrics research 2008–2010 in Handbook Iris Recognition. Springer-Verlag, London. https://doi.org/10.1007/978-1-4471-4402-1_2
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