Deep Biometrics, 1st ed. 2020 Unsupervised and Semi-Supervised Learning Series
Coordonnateurs : Jiang Richard, Li Chang-Tsun, Crookes Danny, Meng Weizhi, Rosenberger Christophe
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 biometrics.
Richard Jiang is currently a Senior Lecturer (Associate Professor) in the School of Computing & Communications at Lancaster University, UK. Previously, he was a senior lecturer (2013-2019) in the Department of Computer Science and Digital Technologies at Northumbria University, Newcastle, UK. He is a Fellow of HEA, an Associate Member of EPSRC College, and a recognized EPSRC RISE Connector. Dr Jiang's research interest mainly resides in the fields of Biometrics, Privacy & Security, Intelligent Systems, and Biomedical Image Analysis. His recent research has been supported by grants from Qatar National Research Fund (NPRP No.8–140-2–065), EPSRC (EP/P009727/1), Leverhulme Trust (RF-2019-492) and other industry/international funders. He has supervised and co-supervised over 10 PhD students. He authored over 60 publications and three Springer books. He served as TPC member and the reviewer for various conferences and journals.
Professor Chang-Tsun Li received a BSc degree in electrical engineering from National Defense University, Taiwan, the MSc degree in computer science from U.S. Naval Postgraduate School, USA, and the PhD degree in computer science from the University of Warwick, UK. He is currently Professor of Cyber Security at Deakin University and Director of Research of Deakin’s Cyber Security Research and Innovation Centre (CSRI). He has had over 20 years of research experience in multimedia forensics and security, biometrics, machine learning, data analytics, computer vision, image processing, pattern recognition, bioinformatics and content-based image retrieval. The outcomes of his research have been translated into award-winning commercial products protected bya series of international patents and have been used by a number of law enforcement agencies, national security institutions and companies around the world, including INTERPOL (Lyon, France), UK Home Office, Metropolitan Police Service (UK), Sussex Police Service (UK), Guildford Cr
Date de parution : 08-2021
Ouvrage de 320 p.
15.5x23.5 cm
Date de parution : 01-2020
Ouvrage de 320 p.
15.5x23.5 cm
Thèmes de Deep Biometrics :
Mots-clés :
Deep Learned Biometric; Convolutional Neural networks; Biometrics in Cybersecurity; Medical/Healthcare Biometrics; Biometrics in Social Computing; Deep Face Detection; Recognition; Morphing; Deep Learned Iris; Fingerprints; Palmprints; Cancellable Biometrics with Deep Learning; Big data issues in Biometrics; Biometrics for Internet of things
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