Deep Learning in Biometrics

Deep Learning in Biometrics
ISBN-10: 1138578231
ISBN-13: 9781138578234
Edition 版本:‏ 1
Released: 2018-03-12
Pages: 328 pages
5
Deep Learning is now synonymous with applied machine learning. Many technology giants (e.g. Google,Microsoft,Apple,IBM) as well as start-ups are focusing on deep learning-based techniques for data analytics and artificial intelligence. This technology applies quite strongly to biometrics. This book covers topics in deep learning,namely convolutional neural networks,deep belief network and stacked autoencoders. The focus is also on the application of these techniques to various biometric modalities: face,iris,palmprint,and fingerprints,while examining the future trends in deep learning and biometric research.
Contributors
1: Deep Learning: Fundamentals and Beyond
2: Unconstrained Face ldentification and Verification
Using Deep Convolutional Features
3: Deep Siamese Convolutional Neural Networks for
Identical Twins and Look-Alike Identification
4: Tackling the Optimization and Precision Weakness of
Deep Cascaded Regression for Facial Key-Point
Localization
5: Learning Deep Metrics for Person Reidentification
6: Deep Face-Representation Learning for Kinship
Verification
7: What’s Hiding in My Deep Features?
8: Stacked Correlation Filters
9: Learning Representations for Unconstrained
Fingerprint Recognition
10: Person ldentification Using Handwriting Dynamics
and Convolutional Neural Networks
11: Counteracting Presentation Attacks in Face,
Fingerprint,and Iris Recognition
12: Fingervein Presentation Attack Detection Using
Transferable Features from Deep Convolution Neural
Networks