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- 000 02025cam a2200373 i 4500
- 008 200215s2020 sz 001 0 eng d
- 040 __ |a EBLCP |b eng |e rda |c EBLCP |d GW5XE |d YDX
- 245 00 |a Deep biometrics / |c Richard Jiang, Chang-Tsun Li, Danny Crookes, Weizhi Meng, Christophe Rosenberger, editors
- 264 _1 |a Cham : |b Springer, |c 2020
- 300 __ |a 322 pages ; |c 24 cm.
- 336 __ |a text |b txt |2 rdacontent
- 337 __ |a unmediated |b n |2 rdamedia
- 338 __ |a volume |b nc |2 rdacarrier
- 490 1_ |a Unsupervised and Semi-Supervised Learning
- 500 __ |a Includes index.
- 520 __ |a 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.
- 650 _0 |a Biometric identification.
- 650 _0 |a Machine learning.
- 700 1_ |a Jiang, Fengan, |d 1986-, |e editor.
- 700 1_ |a Li, Chang-Tsun, |e editor.
- 700 1_ |a Crookes, Danny, |d 1956-, |e editor.
- 700 1_ |a Meng, Weizhi, |d 1986-, |e editor.
- 700 1_ |a Rosenberger, Christophe, |e editor.
- 830 _0 |a Unsupervised and semi-supervised learning.