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- W2804004214 abstract "Because of the rapid development of mobile devices technology, ease of use and interact with humans. May have found a mobile device most uses in our communications. Mobile devices can carry large amounts of personal and sensitive data, but often left not guaranteed (pin) locks are inconvenient to use and thus have seen low adoption while biometrics is more convenient and less susceptible to fraud and manipulation. Were propose in this paper authentication technique for using a mobile face recognition based on cellular neural networks [1] and fuzzy rules control. The good speed and get recognition rate from applied the proposed system in Android system. The images obtained in real time for 60 persons each person has 20 t0 60 different shot face images (about 3600 images), were the results for (FAR = 0), (FRR = 1.66%), (FER = 1.66) and accuracy = 98.34" @default.
- W2804004214 created "2018-06-01" @default.
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- W2804004214 date "2018-05-01" @default.
- W2804004214 modified "2023-10-18" @default.
- W2804004214 title "Fuzzy-cellular neural network for face recognition HCI Authentication" @default.
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- W2804004214 doi "https://doi.org/10.1088/1742-6596/1003/1/012033" @default.
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