Deep Biometrics

This book highlights research advances in biometrics using deep learning, 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 and soft biometrics, smart cities, big biometric data, biometric banking, medical biometrics, and healthcare biometrics, etc. The goal of this volume is to summarize the recent advances in using Deep Learning in the area of biometric security and privacy. Includes advances in biometric recognition and fusion, such as deep learning, fuzzy approaches, and nonlinear graph embedding; Presents advances in privacy versus security, which becomes more important when big data issues emerge; Introduces biometric applications such as biometric banking, internet of things, cloud computing, and medical biometrics.