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Deep Biometrics - 9783030325824

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

Shipping Cost: 31.31 GBP

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Deep Biometrics - 9783030325824

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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

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