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: Hardback Publisher: Springer Nature Switzerland AG, Switzerland Imprint: Springer Nature Switzerland AG ISBN-13: 9783030325824, 978-3030325824 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: 88.78 GBP
Location: Aldershot
End Time: 2024-11-23T09:16:27.000Z
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Book Title: Deep Biometrics
Number of Pages: 320 Pages
Language: English
Publication Name: Deep Biometrics
Publisher: Springer Nature Switzerland A&G
Publication Year: 2020
Subject: Engineering & Technology, Computer Science, Biology
Item Height: 235 mm
Item Weight: 658 g
Type: Textbook
Author: Weizhi Meng, Chang-Tsun Li, Christophe Rosenberger, Richard Jiang, Danny Crookes
Series: Unsupervised and Semi-Supervised Learning
Item Width: 155 mm
Format: Hardcover