Harajuku Lovers

Deep Biometrics - 9783030325855

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

Shipping Cost: 38.13 GBP

Product Images

Deep Biometrics - 9783030325855

Item Specifics

Return postage will be paid by: Buyer

Returns Accepted: Returns Accepted

After receiving the item, your buyer should cancel the purchase within: 60 days

Return policy details:

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

Recommended

AI and Deep Learning in Biometric Security: Trends, Potential, and Challenges
AI and Deep Learning in Biometric Security: Trends, Potential, and Challenges

$153.48

View Details
Deep Learning in Biometrics by Mayank Vatsa
Deep Learning in Biometrics by Mayank Vatsa

$129.24

View Details
3D Facial Recognition Biometric Fingerprint Wifi Remote Control Smart Door Lock
3D Facial Recognition Biometric Fingerprint Wifi Remote Control Smart Door Lock

$232.24

View Details
Deep Biometrics, Hardcover by Jiang, Richard (EDT); Li, Chang-tsun (EDT); Cro...
Deep Biometrics, Hardcover by Jiang, Richard (EDT); Li, Chang-tsun (EDT); Cro...

$173.63

View Details
Advanced Biometrics with Deep Learning by Andrew Teoh Beng Jin
Advanced Biometrics with Deep Learning by Andrew Teoh Beng Jin

$59.47

View Details
AI and Deep Learning in Biometric Security: Trends, Potential, and Challenges
AI and Deep Learning in Biometric Security: Trends, Potential, and Challenges

$135.77

View Details
Deep Biometrics - 9783030325824
Deep Biometrics - 9783030325824

$114.74

View Details
FIREGEAR Gun Safe Biometric Pistol Safe, Quick Access Handgun Deep Black
FIREGEAR Gun Safe Biometric Pistol Safe, Quick Access Handgun Deep Black

$307.99

View Details
AI and Deep Learning in Biometric Security: Trends, Potential, and Challenges by
AI and Deep Learning in Biometric Security: Trends, Potential, and Challenges by

$85.94

View Details
 Deep Learning in Biometrics by Mayank Vatsa 9781138578234 NEW Hard Cover
Deep Learning in Biometrics by Mayank Vatsa 9781138578234 NEW Hard Cover

$201.42

View Details