Deep Learning for Biometrics - Rilegato

 
9783319616568: Deep Learning for Biometrics
Rilegato
ISBN 10: 3319616560 ISBN 13: 9783319616568
Casa editrice: Springer-Nature New York Inc, 2017

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull?autore

Dr. Bir Bhanu is Bourns Presidential Chair, Distinguished Professor of Electrical and Computer Engineering and the Director of the Center for Research in Intelligent Systems at the University of California at Riverside, USA. Some of his other Springer publications include the titles Video Bioinformatics, Distributed Video Sensor Networks, and Human Recognition at a Distance in Video.

Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University.

Dalla quarta di copertina

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.

    Dr. Bir Bhanu is Bourns Presidential Chair, Distinguished Professor of Electrical and Computer Engineering and the Director of the Center for Research in Intelligent Systems at the University of California at Riverside, USA. Some of his other Springer publications include the titles Video Bioinformatics, Distributed Video Sensor Networks, and Human Recognition at a Distance in Video. Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University.

    Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

    Editore
    Springer-Nature New York Inc
    Data di pubblicazione
    2017
    Lingua
    Inglese
    ISBN 10 
    3319616560
    ISBN 13 
    9783319616568
    Rilegatura
    Copertina rigida
    Numero edizione
    1
    Numero di pagine
    312
    Redattore
    Bhanu Bir, Kumar Ajay
    Contatto del produttore
    Elevation
    https://www.also.com/ec/cms5/en_6000/6000/index.jsp

    Friedrich-Karl-Str. 9
    Hamburg
    22391
    Germania

    Altre edizioni note dello stesso titolo

    9783319871288: Deep Learning for Biometrics

    Edizione in evidenza

    ISBN 10:  3319871285 ISBN 13:  9783319871288
    Casa editrice: Springer-Nature New York Inc, 2018
    Brossura