Advanced Biometrics with Deep Learning

Von:

Jin, Andrew [HerausgeberIn]

Mitwirkende(r):

Leng, Lu [HerausgeberIn]

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Verlag: Basel, Switzerland : MDPI - Multidisciplinary Digital Publishing Institute, 2020Beschreibung: 1 Online-Ressource (210 p.)ISBN:

9783039366989
9783039366996

Schlagwörter:

History of engineering & technology

Online-Ressourcen:

Volltext frei verfügbar

Zusammenfassung: Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation learning approach has been shown to be a promising alternative to conventional data-agnostic and handcrafted pre-processing and feature extraction for biometric systems. Furthermore, deep learning offers an end-to-end learning paradigm to unify preprocessing, feature extraction, and recognition, based solely on biometric data. This Special Issue has collected 12 high-quality, state-of-the-art research papers that deal with challenging issues in advanced biometric systems based on deep learning. The 12 papers can be divided into 4 categories according to biometric modality; namely, face biometrics, medical electronic signals (EEG and ECG), voice print, and othersPPN: PPN: 1778432425Package identifier: Produktsigel: ZDB-94-OAB

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