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Deep biometrics

Jiang, Richard.

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Deep biometrics

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deep biometrics/ edited by Richard Jiang ... [et al.].
other author:	Jiang, Richard.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	viii, 320 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction -- Part I - New Methods in Biometrics -- Deep Biometrics: A Robust Approach to Biometrics in Big Data Issues -- Deep Fusion of Multimodal Biometrics -- Deep Fuzzy Logic for Precise Biometric Systems -- Hierarchical Biometric Verification with Deep Sparse Features -- GAN-based Deep Biometric Verification -- Part II - New Advances in Deep Biometrics -- Deep Paleographic Handwriting Analysis for Author Identification -- Deep Palmprints versus Fingerprints: Rivals or Friends? -- A Survey on Deep Soft Biometrics for Forensic Analysis -- Robust Biometric Verification with Low Quality Data -- Deep Solution for Biometric Big Data -- Deep Privacy in Biometric -- Part III - New Biometric Applications using Deep Learning -- Biometric Key Generation via Deep Learning for Mobile Banking -- Securing Electronic Medical Records Using Deep Biometric Authentication -- Deep Body Biometrics from MRI Images for Medicine Advice -- Deep Social Identity in Social Network -- Deep Cognition in Robotic Biometrics -- Conclusion.
Contained By:	Springer eBooks
Subject:	Biometric identification. -
Online resource:	https://doi.org/10.1007/978-3-030-32583-1
ISBN:	9783030325831

Deep biometrics
Deep biometrics[electronic resource] /edited by Richard Jiang ... [et al.]. - Cham :Springer International Publishing :2020. - viii, 320 p. :ill., digital ;24 cm. - Unsupervised and semi-supervised learning,2522-848X. - Unsupervised and semi-supervised learning..

Introduction -- Part I - New Methods in Biometrics -- Deep Biometrics: A Robust Approach to Biometrics in Big Data Issues -- Deep Fusion of Multimodal Biometrics -- Deep Fuzzy Logic for Precise Biometric Systems -- Hierarchical Biometric Verification with Deep Sparse Features -- GAN-based Deep Biometric Verification -- Part II - New Advances in Deep Biometrics -- Deep Paleographic Handwriting Analysis for Author Identification -- Deep Palmprints versus Fingerprints: Rivals or Friends? -- A Survey on Deep Soft Biometrics for Forensic Analysis -- Robust Biometric Verification with Low Quality Data -- Deep Solution for Biometric Big Data -- Deep Privacy in Biometric -- Part III - New Biometric Applications using Deep Learning -- Biometric Key Generation via Deep Learning for Mobile Banking -- Securing Electronic Medical Records Using Deep Biometric Authentication -- Deep Body Biometrics from MRI Images for Medicine Advice -- Deep Social Identity in Social Network -- Deep Cognition in Robotic Biometrics -- Conclusion.

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, such as 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 biometrics.

ISBN: 9783030325831

Standard No.: 10.1007/978-3-030-32583-1doiSubjects--Topical Terms:

729691
Biometric identification.

LC Class. No.: TK7882.B56 / D447 2020

Dewey Class. No.: 006.248

Deep biometrics
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245 0 0 $a Deep biometrics $h [electronic resource] / $c edited by Richard Jiang ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a viii, 320 p. : $b ill., digital ; $c 24 cm.
490 1 $a Unsupervised and semi-supervised learning, $x 2522-848X
505 0 $a Introduction -- Part I - New Methods in Biometrics -- Deep Biometrics: A Robust Approach to Biometrics in Big Data Issues -- Deep Fusion of Multimodal Biometrics -- Deep Fuzzy Logic for Precise Biometric Systems -- Hierarchical Biometric Verification with Deep Sparse Features -- GAN-based Deep Biometric Verification -- Part II - New Advances in Deep Biometrics -- Deep Paleographic Handwriting Analysis for Author Identification -- Deep Palmprints versus Fingerprints: Rivals or Friends? -- A Survey on Deep Soft Biometrics for Forensic Analysis -- Robust Biometric Verification with Low Quality Data -- Deep Solution for Biometric Big Data -- Deep Privacy in Biometric -- Part III - New Biometric Applications using Deep Learning -- Biometric Key Generation via Deep Learning for Mobile Banking -- Securing Electronic Medical Records Using Deep Biometric Authentication -- Deep Body Biometrics from MRI Images for Medicine Advice -- Deep Social Identity in Social Network -- Deep Cognition in Robotic Biometrics -- Conclusion.
520 $a 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, such as 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 biometrics.
650 0 $a Biometric identification. $3 729691
650 0 $a Machine learning. $3 533906
650 1 4 $a Signal, Image and Speech Processing. $3 891073
650 2 4 $a Security. $3 3134865
650 2 4 $a Bioinformatics. $3 553671
650 2 4 $a Biometrics. $3 898232
700 1 $a Jiang, Richard. $3 3219545
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830 0 $a Unsupervised and semi-supervised learning. $3 3380848
856 4 0 $u https://doi.org/10.1007/978-3-030-32583-1
950 $a Engineering (Springer-11647)