Description: Deep Biometrics Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Richard Jiang, Chang-Tsun Li, Danny Crookes, Weizhi Meng, Christophe Rosenberger Format: Paperback Publisher: Springer Nature Switzerland AG, Switzerland Imprint: Springer Nature Switzerland AG ISBN-13: 9783030325855, 978-3030325855 Synopsis 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.
Price: 88.36 GBP
Location: Aldershot
End Time: 2024-11-26T08:55:38.000Z
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Book Title: Deep Biometrics
Item Height: 235 mm
Item Width: 155 mm
Series: Unsupervised and Semi-Supervised Learning
Author: Christophe Rosenberger, Danny Crookes, Weizhi Meng, Richard Jiang, Chang-Tsun Li
Publication Name: Deep Biometrics
Format: Paperback
Language: English
Publisher: Springer Nature Switzerland A&G
Subject: Engineering & Technology, Computer Science, Biology
Publication Year: 2021
Type: Textbook
Item Weight: 504 g
Number of Pages: 320 Pages