Dublin Core
Title
Advanced Biometrics with Deep Learning
Subject
Technology
Engineering
Description
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.
Creator
Jin, Andrew (editor)
Leng, Lu (editor)
Source
https://directory.doabooks.org/handle/20.500.12854/68869
Publisher
MDPI - Multidisciplinary Digital Publishing Institute
Date
2020
Rights
https://creativecommons.org/licenses/by/4.0/
Format
Pdf
Language
English
Type
Book
Identifier
10.3390/books978-3-03936-699-6