Multimodal Biometric and Machine Learning Technologies: Applications for Computer Vision
- 4h 36m
- Arpit Jain, Deepika Ghai, Sandeep Kumar, Shilpa Rani, Suman Lata Tripathi
- John Wiley & Sons (US)
- 2023
MULTIMODAL BIOMETRIC AND MACHINE LEARNING TECHNOLOGIES
With an increasing demand for biometric systems in various industries, this book on multimodal biometric systems, answers the call for increased resources to help researchers, developers, and practitioners.
Multimodal biometric and machine learning technologies have revolutionized the field of security and authentication. These technologies utilize multiple sources of information, such as facial recognition, voice recognition, and fingerprint scanning, to verify an individual???s identity. The need for enhanced security and authentication has become increasingly important, and with the rise of digital technologies, cyber-attacks and identity theft have increased exponentially. Traditional authentication methods, such as passwords and PINs, have become less secure as hackers devise new ways to bypass them. In this context, multimodal biometric and machine learning technologies offer a more secure and reliable approach to authentication.
This book provides relevant information on multimodal biometric and machine learning technologies and focuses on how humans and computers interact to ever-increasing levels of complexity and simplicity. The book provides content on the theory of multimodal biometric design, evaluation, and user diversity, and explains the underlying causes of the social and organizational problems that are typically devoted to descriptions of rehabilitation methods for specific processes. Furthermore, the book describes new algorithms for modeling accessible to scientists of all varieties.
Audience
Researchers in computer science and biometrics, developers who are designing and implementing biometric systems, and practitioners who are using biometric systems in their work, such as law enforcement personnel or healthcare professionals.
About the Author
Sandeep Kumar, PhD, is a professor in Computer Science & Engineering, Koneru Lakshmaiah Educational Foundation, India, He has published more than 150 journal articles and conference papers, 20 patents, and authored 13 books.
Deepika Ghai, PhD, is an assistant professor at Lovely Professional University, India. She has published more than 35 research papers in refereed journals and conferences. She received the Dr. C.B. Gupta Award in 2021 at Lovely Professional University.
Arpit Jain, PhD, is a professor at the Koneru Lakshmamai University Education Foundation, Vijayawada, A.P., India. He has published more than 40 research papers in international journals, filed 25+ patents as well as authored/edited five books.
Suman Lata Tripathi, PhD, is a professor at Lovely Professional University with more than 21 years of experience in academics. She has published more than 105 research papers in refereed journals and conferences. She has published three books and currently has multiple volumes scheduled for publication from Wiley-Scrivener.
Shilpa Rani, PhD, is an associate professor at the Neil Gogte Institute of Technology, Hyderabad, India, and specializes in computer science & engineering. She has authored seven books, more than 50 journal articles conference papers, as well as 14 patents.
In this Book
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Multimodal Biometric in Computer Vision
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A Vaccine Slot Tracker Model Using Fuzzy Logic for Providing Quality of Service
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Enhanced Text Mining Approach for Better Ranking System of Customer Reviews
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Spatial Analysis of Carbon Sequestration Mapping Using Remote Sensing and Satellite Image Processing
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Applications of Multimodal Biometric Technology
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A Study of Multimodal Colearning, Application in Biometrics and Authentication
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A Structured Review on Virtual Reality Technology Application in the Field of Sports
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A Systematic and Structured Review of Fuzzy Logic-Based Evaluation in Sports
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Machine Learning and Deep Learning for Multimodal Biometrics
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Machine Learning and Deep Learning: Classification and Regression Problems, Recurrent Neural Networks, Convolutional Neural Networks
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Handwriting and Speech-Based Secured Multimodal Biometrics Identification Technique
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Convolutional Neural Network Approach for Multimodal Biometric Recognition System for Banking Sector on Fusion of Face and Finger
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Secured Automated Certificate Creation Based on Multimodal Biometric Verification
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Face and Iris-Based Secured Authorization Model Using CNN
