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Titlebook: Deep Biometrics; Richard Jiang,Chang-Tsun Li,Christophe Rosenberger Book 2020 Springer Nature Switzerland AG 2020 Deep Learned Biometric.C

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书目名称Deep Biometrics
编辑Richard Jiang,Chang-Tsun Li,Christophe Rosenberger
视频video
概述Highlights the impact of deep learning over the field of biometrics in a wide area;.Exploits the deeper and wider background of biometrics, such as privacy versus security, biometric big data, biometr
丛书名称Unsupervised and Semi-Supervised Learning
图书封面Titlebook: Deep Biometrics;  Richard Jiang,Chang-Tsun Li,Christophe Rosenberger Book 2020 Springer Nature Switzerland AG 2020 Deep Learned Biometric.C
描述.This book highlights new advances in biometrics using deep learning toward deeper and wider background, deeming it “Deep Biometrics”. The book aims to highlight recent developments in biometrics using semi-supervised and unsupervised methods such as Deep Neural Networks, Deep Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, and so on. The contributors demonstrate the power of deep learning techniques in the emerging new areas such as privacy and security issues, cancellable biometrics, soft biometrics, smart cities, big biometric data, biometric banking, medical biometrics, healthcare biometrics, and biometric genetics, etc. The goal of this volume is to summarize the recent advances in using Deep Learning in the area of biometric security and privacy toward deeper and wider applications..Highlights the impact of deep learning over the field of biometrics in a wide area;.Exploits the deeper and wider background of biometrics, suchas privacy versus security, biometric big data, biometric genetics, and biometric diagnosis, etc.;.Introduces new biometric applications such as biometric banking, internet of things, cloud computing, and medical biometri
出版日期Book 2020
关键词Deep Learned Biometric; Convolutional Neural networks; Biometrics in Cybersecurity; Medical/Healthcare
版次1
doihttps://doi.org/10.1007/978-3-030-32583-1
isbn_softcover978-3-030-32585-5
isbn_ebook978-3-030-32583-1Series ISSN 2522-848X Series E-ISSN 2522-8498
issn_series 2522-848X
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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