Machine Learning for Biometrics Concepts, Algorithms and Applications
Aus der Reihe
Cognitive Data Science in Sustainable Computing
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Form:Einzelkauf Download
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Sprache:Englisch
113,00 €
inkl. gesetzl. MwSt.Beschreibung
Produktdetails
Format
ePUB 3
Kopierschutz
Nein
Family Sharing
Nein
Text-to-Speech
Ja
Erscheinungsdatum
21.01.2022
Herausgeber
Partha Pratim Sarangi + weitereVerlag
Elsevier Science & Techn.Seitenzahl
264 (Printausgabe)
Dateigröße
52516 KB
Sprache
Englisch
EAN
9780323903394
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
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
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