Deep Learning in Biometrics

Nonfiction, Science & Nature, Technology, Imaging Systems, Computers, Advanced Computing, Theory, Database Management
Cover of the book Deep Learning in Biometrics by , CRC Press
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Author: ISBN: 9781351264983
Publisher: CRC Press Publication: March 5, 2018
Imprint: CRC Press Language: English
Author:
ISBN: 9781351264983
Publisher: CRC Press
Publication: March 5, 2018
Imprint: CRC Press
Language: English

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.

  • Contains chapters written by authors who are leading researchers in biometrics.
  • Presents a comprehensive overview on the internal mechanisms of deep learning.
  • Discusses the latest developments in biometric research.
  • Examines future trends in deep learning and biometric research.
  • Provides extensive references at the end of each chapter to enhance further study.
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

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