Deep Learning In Biometrics
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Deep Learning In Biometrics
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Author : Mayank Vatsa
language : en
Publisher: CRC Press
Release Date : 2018-03-05
Deep Learning In Biometrics written by Mayank Vatsa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-05 with Computers categories.
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.
Deep Learning For Biometrics
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Author : Bir Bhanu
language : en
Publisher: Springer
Release Date : 2017-08-01
Deep Learning For Biometrics written by Bir Bhanu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-01 with Computers categories.
This timely text/reference presents a broad overview of advanced deep learning architectures for learning effective feature representation for perceptual and biometrics-related tasks. The text offers a showcase of cutting-edge research on the use of convolutional neural networks (CNN) in face, iris, fingerprint, and vascular biometric systems, in addition to surveillance systems that use soft biometrics. Issues of biometrics security are also examined. Topics and features: addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities; revisits deep learning for face biometrics, offering insights from neuroimaging, and provides comparison with popular CNN-based architectures for face recognition; examines deep learning for state-of-the-art latent fingerprint and finger-vein recognition, as well as iris recognition; discusses deep learning for soft biometrics, including approaches for gesture-based identification, gender classification, and tattoo recognition; investigates deep learning for biometrics security, covering biometrics template protection methods, and liveness detection to protect against fake biometrics samples; presents contributions from a global selection of pre-eminent experts in the field representing academia, industry and government laboratories. Providing both an accessible introduction to the practical applications of deep learning in biometrics, and a comprehensive coverage of the entire spectrum of biometric modalities, this authoritative volume will be of great interest to all researchers, practitioners and students involved in related areas of computer vision, pattern recognition and machine learning.
Ai And Deep Learning In Biometric Security
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Author : Gaurav Jaswal
language : en
Publisher: CRC Press
Release Date : 2021-03-21
Ai And Deep Learning In Biometric Security written by Gaurav Jaswal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-21 with Computers categories.
This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.
Advanced Biometrics With Deep Learning
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Author : Andrew Jin
language : en
Publisher:
Release Date : 2020
Advanced Biometrics With Deep Learning written by Andrew Jin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation learning approach has been shown to be a promising alternative to conventional data-agnostic and handcrafted pre-processing and feature extraction for biometric systems. Furthermore, deep learning offers an end-to-end learning paradigm to unify preprocessing, feature extraction, and recognition, based solely on biometric data. This Special Issue has collected 12 high-quality, state-of-the-art research papers that deal with challenging issues in advanced biometric systems based on deep learning. The 12 papers can be divided into 4 categories according to biometric modality; namely, face biometrics, medical electronic signals (EEG and ECG), voice print, and others.
Machine Learning For Biometrics
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Author : Partha Pratim Sarangi
language : en
Publisher: Elsevier
Release Date : 2022-01-24
Machine Learning For Biometrics written by Partha Pratim Sarangi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-24 with Computers categories.
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
Deep Learning Approaches To Cloud Security
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Author : Pramod Singh Rathore
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-26
Deep Learning Approaches To Cloud Security written by Pramod Singh Rathore and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-26 with Technology & Engineering categories.
DEEP LEARNING APPROACHES TO CLOUD SECURITY Covering one of the most important subjects to our society today, cloud security, this editorial team delves into solutions taken from evolving deep learning approaches, solutions allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Deep learning is the fastest growing field in computer science. Deep learning algorithms and techniques are found to be useful in different areas like automatic machine translation, automatic handwriting generation, visual recognition, fraud detection, and detecting developmental delay in children. However, applying deep learning techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. This book provides state of the art approaches of deep learning in these areas, including areas of detection and prediction, as well as future framework development, building service systems and analytical aspects. In all these topics, deep learning approaches, such as artificial neural networks, fuzzy logic, genetic algorithms, and hybrid mechanisms are used. This book is intended for dealing with modeling and performance prediction of the efficient cloud security systems, thereby bringing a newer dimension to this rapidly evolving field. This groundbreaking new volume presents these topics and trends of deep learning, bridging the research gap, and presenting solutions to the challenges facing the engineer or scientist every day in this area. Whether for the veteran engineer or the student, this is a must-have for any library. Deep Learning Approaches to Cloud Security: Is the first volume of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches Covers these important new innovations, such as AI, data mining, and other evolving computing technologies in relation to cloud security Is a useful reference for the veteran computer scientist or engineer working in this area or an engineer new to the area, or a student in this area Discusses not just the practical applications of these technologies, but also the broader concepts and theory behind how these deep learning tools are vital not just to cloud security, but society as a whole Audience: Computer scientists, scientists and engineers working with information technology, design, network security, and manufacturing, researchers in computers, electronics, and electrical and network security, integrated domain, and data analytics, and students in these areas
Advanced Biometrics With Deep Learning
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Author : Andrew Teoh Beng Jin
language : en
Publisher: MDPI
Release Date : 2020-12-28
Advanced Biometrics With Deep Learning written by Andrew Teoh Beng Jin and has been published by MDPI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-28 with Business & Economics categories.
Biometrics, such as fingerprint, iris, face, hand print, hand vein, speech and gait recognition, etc., as a means of identity management have become commonplace nowadays for various applications. Biometric systems follow a typical pipeline, that is composed of separate preprocessing, feature extraction and classification. Deep learning as a data-driven representation learning approach has been shown to be a promising alternative to conventional data-agnostic and handcrafted pre-processing and feature extraction for biometric systems. Furthermore, deep learning offers an end-to-end learning paradigm to unify preprocessing, feature extraction, and recognition, based solely on biometric data. This Special Issue has collected 12 high-quality, state-of-the-art research papers that deal with challenging issues in advanced biometric systems based on deep learning. The 12 papers can be divided into 4 categories according to biometric modality; namely, face biometrics, medical electronic signals (EEG and ECG), voice print, and others.
Design And Implementation Of Healthcare Biometric Systems
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Author : Kisku, Dakshina Ranjan
language : en
Publisher: IGI Global
Release Date : 2019-01-11
Design And Implementation Of Healthcare Biometric Systems written by Kisku, Dakshina Ranjan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-11 with Medical categories.
Healthcare sectors often deal with a large amount of data related to patients’ care and hospital workforce management. Mistakes occur, and the impending results are disastrous for individuals’ personal identity information. However, an innovative and reliable way to safeguard the identity of individuals and provide protection of medical records from criminals is already in effect. Design and Implementation of Healthcare Biometric Systems provides innovative insights into medical identity theft and the benefits behind biometrics technologies that could be offered to protect medical records from hackers and malicious users. The content within this publication represents the work of ASD screening systems, healthcare management, and patient rehabilitation. It is designed for educators, researchers, faculty members, industry practitioners, graduate students, and professionals working with healthcare services and covers topics centered on understanding the practical essence of next-generation healthcare biometrics systems and future research directions.
Ai And Deep Learning In Biometric Security
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Author : Gaurav Jaswal
language : en
Publisher: CRC Press
Release Date : 2021-03-22
Ai And Deep Learning In Biometric Security written by Gaurav Jaswal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-22 with Technology & Engineering categories.
This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.