Deep Learning for Biometrics (Advances in Computer Vision and Pattern Recognition)
ISBN-13:
9783319616568
ISBN-10:
3319616560
Edition:
1st ed. 2017
Author:
Ajay Kumar, Bir Bhanu
Publication date:
2017
Publisher:
Springer
Format:
Hardcover
343 pages
Category:
AI & Machine Learning
,
Computer Science
FREE US shipping
Book details
ISBN-13:
9783319616568
ISBN-10:
3319616560
Edition:
1st ed. 2017
Author:
Ajay Kumar, Bir Bhanu
Publication date:
2017
Publisher:
Springer
Format:
Hardcover
343 pages
Category:
AI & Machine Learning
,
Computer Science
Summary
Deep Learning for Biometrics (Advances in Computer Vision and Pattern Recognition) (ISBN-13: 9783319616568 and ISBN-10: 3319616560), written by authors
Ajay Kumar, Bir Bhanu, was published by Springer in 2017.
With an overall rating of 4.1 stars, it's a notable title among other
AI & Machine Learning
(Computer Science) books. You can easily purchase or rent Deep Learning for Biometrics (Advances in Computer Vision and Pattern Recognition) (Hardcover) from BooksRun,
along with many other new and used
AI & Machine Learning
books
and textbooks.
And, if you're looking to sell your copy, our current buyback offer is $0.3.
Description
This timely text/reference presents a broad overview of advanced deep learning architectures for learning effective feature representation for perceptual and biometrics-related tasks. The text offers a showcase of cutting-edge research on the use of convolutional neural networks (CNN) in face, iris, fingerprint, and vascular biometric systems, in addition to surveillance systems that use soft biometrics. Issues of biometrics security are also examined.
Topics and features: addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities; revisits deep learning for face biometrics, offering insights from neuroimaging, and provides comparison with popular CNN-based architectures for face recognition; examines deep learning for state-of-the-art latent fingerprint and finger-vein recognition, as well as iris recognition; discusses deep learning for soft biometrics, including approaches for gesture-based identification, gender classification, and tattoo recognition; investigates deep learning for biometrics security, covering biometrics template protection methods, and liveness detection to protect against fake biometrics samples; presents contributions from a global selection of pre-eminent experts in the field representing academia, industry and government laboratories.Providing both an accessible introduction to the practical applications of deep learning in biometrics, and a comprehensive coverage of the entire spectrum of biometric modalities, this authoritative volume will be of great interest to all researchers, practitioners and students involved in related areas of computer vision, pattern recognition and machine learning.We would LOVE it if you could help us and other readers by reviewing the book
Book review
Congratulations! We have received your book review.
{user}
{createdAt}
by {truncated_author}