Deep Learning for Biometrics Front Cover

Deep Learning for Biometrics

  • Length: 312 pages
  • Edition: 1st ed. 2017
  • Publisher:
  • Publication Date: 2017-09-03
  • ISBN-10: 3319616560
  • ISBN-13: 9783319616568
  • Sales Rank: #2619088 (See Top 100 Books)
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.

Table of Contents

Chapter 1 The Functional Neuroanatomy Of Face Processing: Insights From Neuroimaging And Implications For Deep Learning
Chapter 2 Real-Time Face Identification Via Multi-Convolutional Neural Network And Boosted Hashing Forest
Chapter 3 Cms-Rcnn: Contextual Multi-Scale Region-Based Cnn For Unconstrained Face Detection
Chapter Deep Learning For Fingerprint, Fingervein And Iris Recognition
Chapter 4 Latent Fingerprint Image Segmentation Using Deep Neural Network
Chapter 5 Finger Vein Identification Using Convolutional Neural Network And Supervised Discrete Hashing
Chapter 6 Iris Segmentation Using Fully Convolutional Encoder–Decoder Networks
Chapter Deep Learning For Soft Biometrics
Chapter 7 Two-Stream Cnns For Gesture-Based Verification And Identification: Learning User Style
Chapter 8 Deepgender2: A Generative Approach Toward Occlusion And Low-Resolution Robust Facial Gender Classification Via Progressively Trained Attention Shift Convolutional Neural Networks (Ptas-Cnn) And Deep Convolutional Generative Adversarial Networks (Dcgan)
Chapter 9 Gender Classification From Nir Iris Images Using Deep Learning
Chapter 10 Deep Learning For Tattoo Recognition
Chapter Deep Learning For Biometrics Security And Protection
Chapter 11 Learning Representations For Cryptographic Hash Based Face Template Protection
Chapter 12 Deep Triplet Embedding Representations For Liveness Detection

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