Advanced Biometrics with Deep Learning

ISBN 10: 303936698X / ISBN 13: 9783039366989

Edité par Mdpi AG, 2020

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Détails bibliographiques

• Titre: Advanced Biometrics with Deep Learning
• Éditeur: Mdpi AG
• Date de parution: 2020
• Langue: anglais
• ISBN à 10 chiffres: 303936698X
• ISBN à 13 chiffres: 9783039366989
• Reliure: Couverture rigide
• État de l'article: New

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Synopsis

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 others.