Common biometric systems like fingerprint and face recognition are more convenient in daily applications, but biological and behavioral characteristics of the biometrics features can be fabricated and digitally stolen. Thus, biometrics features with liveness detection such as the electrocardiogram (ECG) have been introduced as its features are hidden and difficult to forge. This study presents a review of ECG biometrics based on deep learning and generalization issues in deep learning. Based on the review, deep learning methods such as recurrent neural networks (RNN) and long short-term memory networks (LSTM) with attention mechanisms can be employed to improve the performance and generalization ability of ECG biometrics systems.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    A Review of ECG Biometrics: Generalization in Deep Learning with Attention Mechanisms


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Ahmad, Nur Syazreen (Herausgeber:in) / Mohamad-Saleh, Junita (Herausgeber:in) / Teh, Jiashen (Herausgeber:in) / Saod, Aini Hafizah Mohd (Autor:in) / Ramli, Dzati Athiar (Autor:in)

    Kongress:

    International Conference on Robotics, Vision, Signal Processing and Power Applications ; 2021 April 05, 2021 - April 06, 2021



    Erscheinungsdatum :

    31.03.2024


    Format / Umfang :

    6 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch







    Hand biometrics

    Yoruk, E. / Dutagaci, H. / Sankur, B. | British Library Online Contents | 2006


    Crop biometrics detection

    PAPANIKOLOPOULOS NIKOLAOS / MORELLAS VASSILIOS / ZERMAS DIMITRIS et al. | Europäisches Patentamt | 2021

    Freier Zugriff