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Finger-Knuckle-Print Recognition Using Deep Convolutional Neural Network

Abstract : Biometric technology has become essential in our daily life. In such a biometric system, personal identification is based on behavioral or biological characteristics. Recently, the trait of the Finger-Knuckle-Print (FKP) is used due to its ease of use and low cost. In order to develop an efficient recognition system based on these images, we propose a deep learning method where we use our own Convolutional Neural Network (CNN) to identify persons. Excellent results were conducted with unimodal and multimodal identification systems.
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https://hal-uphf.archives-ouvertes.fr/hal-03566713
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Submitted on : Friday, February 11, 2022 - 4:50:43 PM
Last modification on : Wednesday, March 23, 2022 - 3:51:16 PM

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Selma Trabelsi, Djamel Samai, Abdallah Meraoumia, Khaled Bensid, Azeddine Benlamoudi, et al.. Finger-Knuckle-Print Recognition Using Deep Convolutional Neural Network. 1st International Conference on Communications, Control Systems and Signal Processing (CCSSP 2020 ), May 2020, EL OUED, Algeria. pp.163-168, ⟨10.1109/CCSSP49278.2020.9151531⟩. ⟨hal-03566713⟩

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