Machine Learning for Biometrics: Concepts, Algorithms and Applications

Machine Learning for Biometrics: Concepts, Algorithms and Applications book cover

Machine Learning for Biometrics: Concepts, Algorithms and Applications

Author(s): Partha Pratim Sarangi (Editor), Madhumita Panda (Editor), Subhashree Mishra (Editor), Bhabani Shankar Prasad Mishra (Editor), Banshidhar Majhi (Editor)

  • Publisher: Academic Press
  • Publication Date: 28 Jan. 2022
  • Language: English
  • Print length: 264 pages
  • ISBN-10: 0323852092
  • ISBN-13: 9780323852098

Book Description

Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can be adopted in this direction. Each chapter of the volume is supported by real-life case studies, illustrative examples and video demonstrations. The book elucidates various biometric concepts, algorithms and applications with machine intelligence solutions, providing guidance on best practices for new technologies such as e-health solutions, Data science, Cloud computing, and Internet of Things, etc.

In each section, different machine learning concepts and algorithms are used, such as different object detection techniques, image enhancement techniques, both global and local feature extraction techniques, and classifiers those are commonly used data science techniques. These biometrics techniques can be used as tools in Cloud computing, Mobile computing, IOT based applications, and e-health care systems for secure login, device access control, personal recognition and surveillance.

  • Covers different machine intelligence concepts, algorithms and applications in the field of cybersecurity, e-health monitoring, secure cloud computing and secure IOT based operations
  • Explores advanced approaches to improve recognition performance of biometric systems with the use of recent machine intelligence techniques
  • Introduces detection or segmentation techniques to detect biometric characteristics from the background in the input sample

Editorial Reviews

Review

Provides fundamental information on the up-to-date concepts and algorithms of biometrics used in personal recognition

From the Back Cover

Biometrics is essentially a pattern recognition technique. It has four major parts: biometric trait detection, preprocessing, feature extraction, and recognition. In each part different machine learning concepts and algorithms are used such as different object detection techniques, image enhancement techniques, both global and local feature extraction techniques, and classifiers those are commonly used data science techniques. These biometrics techniques can be used as tools in Cloud computing, Mobile computing, IOT based applications, and e-health care systems for secure login, device access control, personal recognition, and surveillance.

Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics, followed by a review of intelligent and cognitive learning tools which can be adopted in this direction. Each chapter of the volume is supported by real life case studies, illustrative examples and video demonstrations.

This book elucidates various biometric concepts, algorithms and applications with machine intelligence solutions. It would provide guidance on the best practices for new technologies such as e-health solutions, Data science, Cloud computing, and Internet of Things, etc.

View on Amazon

电子书代发PDF格式价格30我要求助
未经允许不得转载:Wow! eBook » Machine Learning for Biometrics: Concepts, Algorithms and Applications