Deep Learning For Biometrics

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Deep Learning for Biometrics

Author : Bir Bhanu
Publisher : Springer
ISBN 13 : 9783319871288
Total Pages : 0 pages
Book Rating : 4.8/5 (712 download)

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Book Synopsis Deep Learning for Biometrics by : Bir Bhanu

Download or read book Deep Learning for Biometrics written by Bir Bhanu and published by Springer. This book was released on 2018-05-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning in Biometrics

Author : Mayank Vatsa
Publisher : CRC Press
ISBN 13 : 1351264990
Total Pages : 316 pages
Book Rating : 4.3/5 (512 download)

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Book Synopsis Deep Learning in Biometrics by : Mayank Vatsa

Download or read book Deep Learning in Biometrics written by Mayank Vatsa and published by CRC Press. This book was released on 2018-03-05 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning for Biometrics

Author : Partha Pratim Sarangi
Publisher : Academic Press
ISBN 13 : 0323903398
Total Pages : 266 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Machine Learning for Biometrics by : Partha Pratim Sarangi

Download or read book Machine Learning for Biometrics written by Partha Pratim Sarangi and published by Academic Press. This book was released on 2022-01-21 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

AI and Deep Learning in Biometric Security

Author : Gaurav Jaswal
Publisher : CRC Press
ISBN 13 : 1000291669
Total Pages : 409 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis AI and Deep Learning in Biometric Security by : Gaurav Jaswal

Download or read book AI and Deep Learning in Biometric Security written by Gaurav Jaswal and published by CRC Press. This book was released on 2021-03-22 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning and Biometrics

Author : Jucheng Yang
Publisher : BoD – Books on Demand
ISBN 13 : 1789235901
Total Pages : 148 pages
Book Rating : 4.7/5 (892 download)

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Book Synopsis Machine Learning and Biometrics by : Jucheng Yang

Download or read book Machine Learning and Biometrics written by Jucheng Yang and published by BoD – Books on Demand. This book was released on 2018-08-29 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: We are entering the era of big data, and machine learning can be used to analyze this deluge of data automatically. Machine learning has been used to solve many interesting and often difficult real-world problems, and the biometrics is one of the leading applications of machine learning. This book introduces some new techniques on biometrics and machine learning, and new proposals of using machine learning techniques for biometrics as well. This book consists of two parts: "Biometrics" and "Machine Learning for Biometrics." Parts I and II contain four and three chapters, respectively. The book is reviewed by editors: Prof. Jucheng Yang, Prof. Dong Sun Park, Prof. Sook Yoon, Dr. Yarui Chen, and Dr. Chuanlei Zhang.

Advanced Biometrics with Deep Learning

Author : Andrew Jin
Publisher :
ISBN 13 : 9783039366996
Total Pages : 210 pages
Book Rating : 4.3/5 (669 download)

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Book Synopsis Advanced Biometrics with Deep Learning by : Andrew Jin

Download or read book Advanced Biometrics with Deep Learning written by Andrew Jin and published by . This book was released on 2020 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Human Recognition in Unconstrained Environments

Author : Maria De Marsico
Publisher : Academic Press
ISBN 13 : 0081007124
Total Pages : 250 pages
Book Rating : 4.0/5 (81 download)

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Book Synopsis Human Recognition in Unconstrained Environments by : Maria De Marsico

Download or read book Human Recognition in Unconstrained Environments written by Maria De Marsico and published by Academic Press. This book was released on 2017-01-09 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human Recognition in Unconstrained Environments provides a unique picture of the complete ‘in-the-wild’ biometric recognition processing chain; from data acquisition through to detection, segmentation, encoding, and matching reactions against security incidents. Coverage includes: Data hardware architecture fundamentals Background subtraction of humans in outdoor scenes Camera synchronization Biometric traits: Real-time detection and data segmentation Biometric traits: Feature encoding / matching Fusion at different levels Reaction against security incidents Ethical issues in non-cooperative biometric recognition in public spaces With this book readers will learn how to: Use computer vision, pattern recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and security Choose the most suited biometric traits and recognition methods for uncontrolled settings Evaluate the performance of a biometric system on real world data Presents a complete picture of the biometric recognition processing chain, ranging from data acquisition to the reaction procedures against security incidents Provides specific requirements and issues behind each typical phase of the development of a robust biometric recognition system Includes a contextualization of the ethical/privacy issues behind the development of a covert recognition system which can be used for forensics and security activities

Design and Implementation of Healthcare Biometric Systems

Author : Kisku, Dakshina Ranjan
Publisher : IGI Global
ISBN 13 : 152257526X
Total Pages : 315 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Design and Implementation of Healthcare Biometric Systems by : Kisku, Dakshina Ranjan

Download or read book Design and Implementation of Healthcare Biometric Systems written by Kisku, Dakshina Ranjan and published by IGI Global. This book was released on 2019-01-11 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning Techniques for Gait Biometric Recognition

Author : James Eric Mason
Publisher : Springer
ISBN 13 : 3319290886
Total Pages : 247 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Machine Learning Techniques for Gait Biometric Recognition by : James Eric Mason

Download or read book Machine Learning Techniques for Gait Biometric Recognition written by James Eric Mason and published by Springer. This book was released on 2016-02-04 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reaction Force (GRF)-based Gait Biometrics Recognition framework is proposed and validated by experiments. In addition, an in-depth analysis of existing recognition techniques that are best suited for performing footstep GRF-based person recognition is also proposed, as well as a comparison of feature extractors, normalizers, and classifiers configurations that were never directly compared with one another in any previous GRF recognition research. Finally, a detailed theoretical overview of many existing machine learning techniques is presented, leading to a proposal of two novel data processing techniques developed specifically for the purpose of gait biometric recognition using GRF. This book · introduces novel machine-learning-based temporal normalization techniques · bridges research gaps concerning the effect of footwear and stepping speed on footstep GRF-based person recognition · provides detailed discussions of key research challenges and open research issues in gait biometrics recognition · compares biometrics systems trained and tested with the same footwear against those trained and tested with different footwear

Forensic Investigations and Risk Management in Mobile and Wireless Communications

Author : Sharma, Kavita
Publisher : IGI Global
ISBN 13 : 1522595562
Total Pages : 337 pages
Book Rating : 4.5/5 (225 download)

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Book Synopsis Forensic Investigations and Risk Management in Mobile and Wireless Communications by : Sharma, Kavita

Download or read book Forensic Investigations and Risk Management in Mobile and Wireless Communications written by Sharma, Kavita and published by IGI Global. This book was released on 2019-07-26 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mobile forensics has grown from a relatively obscure tradecraft to a crucial part of many criminal investigations, and is now used daily by examiners and analysts within local, state, and federal law enforcement as well as within the military, US government organizations, and the private “e-Discovery” industry. Developments in forensic research, tools, and processes over the past decade have been very successful and continue to change at a rapid pace. Forensic Investigations and Risk Management in Mobile and Wireless Communications is a collection of innovative research on the methods and applications of analyzing mobile devices and data for collection of information pertaining to the legal evidence related to various security breaches and intrusion detection. While highlighting topics including cybercrime, neural networks, and smartphone security, this book is ideally designed for security analysts, IT professionals, researchers, practitioners, academicians, and students currently investigating the up-and-coming aspects surrounding network security, computer science, and security engineering.

Deep Learning in Biometrics

Author : Mayank Vatsa
Publisher : CRC Press
ISBN 13 : 1351264982
Total Pages : 249 pages
Book Rating : 4.3/5 (512 download)

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Book Synopsis Deep Learning in Biometrics by : Mayank Vatsa

Download or read book Deep Learning in Biometrics written by Mayank Vatsa and published by CRC Press. This book was released on 2018-03-05 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Approaches to Cloud Security

Author : Pramod Singh Rathore
Publisher : John Wiley & Sons
ISBN 13 : 1119760526
Total Pages : 308 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Deep Learning Approaches to Cloud Security by : Pramod Singh Rathore

Download or read book Deep Learning Approaches to Cloud Security written by Pramod Singh Rathore and published by John Wiley & Sons. This book was released on 2022-01-26 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Biometric Authentication

Author : Sun Yuan Kung
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 504 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Biometric Authentication by : Sun Yuan Kung

Download or read book Biometric Authentication written by Sun Yuan Kung and published by Prentice Hall. This book was released on 2005 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: A breakthrough approach to improving biometrics performanceConstructing robust information processing systems for face and voice recognitionSupporting high-performance data fusion in multimodal systemsAlgorithms, implementation techniques, and application examples Machine learning: driving significant improvements in biometric performance As they improve, biometric authentication systems are becoming increasingly indispensable for protecting life and property. This book introduces powerful machine learning techniques that significantly improve biometric performance in a broad spectrum of application domains. Three leading researchers bridge the gap between research, design, and deployment, introducing key algorithms as well as practical implementation techniques. They demonstrate how to construct robust information processing systems for biometric authentication in both face and voice recognition systems, and to support data fusion in multimodal systems. Coverage includes: How machine learning approaches differ from conventional template matchingTheoretical pillars of machine learning for complex pattern recognition and classificationExpectation-maximization (EM) algorithms and support vector machines (SVM)Multi-layer learning models and back-propagation (BP) algorithmsProbabilistic decision-based neural networks (PDNNs) for face biometricsFlexible structural frameworks for incorporating machine learning subsystems in biometric applicationsHierarchical mixture of experts and inter-class learning strategies based on class-based modular networksMulti-cue data fusion techniques that integrate face and voice recognitionApplication case studies

Handbook of Biometric Anti-Spoofing

Author : Sébastien Marcel
Publisher : Springer
ISBN 13 : 3319926276
Total Pages : 522 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Handbook of Biometric Anti-Spoofing by : Sébastien Marcel

Download or read book Handbook of Biometric Anti-Spoofing written by Sébastien Marcel and published by Springer. This book was released on 2019-01-01 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: This authoritative and comprehensive handbook is the definitive work on the current state of the art of Biometric Presentation Attack Detection (PAD) – also known as Biometric Anti-Spoofing. Building on the success of the previous, pioneering edition, this thoroughly updated second edition has been considerably expanded to provide even greater coverage of PAD methods, spanning biometrics systems based on face, fingerprint, iris, voice, vein, and signature recognition. New material is also included on major PAD competitions, important databases for research, and on the impact of recent international legislation. Valuable insights are supplied by a selection of leading experts in the field, complete with results from reproducible research, supported by source code and further information available at an associated website. Topics and features: reviews the latest developments in PAD for fingerprint biometrics, covering optical coherence tomography (OCT) technology, and issues of interoperability; examines methods for PAD in iris recognition systems, and the application of stimulated pupillary light reflex for this purpose; discusses advancements in PAD methods for face recognition-based biometrics, such as research on 3D facial masks and remote photoplethysmography (rPPG); presents a survey of PAD for automatic speaker recognition (ASV), including the use of convolutional neural networks (CNNs), and an overview of relevant databases; describes the results yielded by key competitions on fingerprint liveness detection, iris liveness detection, and software-based face anti-spoofing; provides analyses of PAD in fingervein recognition, online handwritten signature verification, and in biometric technologies on mobile devicesincludes coverage of international standards, the E.U. PSDII and GDPR directives, and on different perspectives on presentation attack evaluation. This text/reference is essential reading for anyone involved in biometric identity verification, be they students, researchers, practitioners, engineers, or technology consultants. Those new to the field will also benefit from a number of introductory chapters, outlining the basics for the most important biometrics.

Biometric Systems

Author : Loris Nanni
Publisher : MDPI
ISBN 13 : 3036511288
Total Pages : 352 pages
Book Rating : 4.0/5 (365 download)

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Book Synopsis Biometric Systems by : Loris Nanni

Download or read book Biometric Systems written by Loris Nanni and published by MDPI. This book was released on 2021-09-01 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study.

Biometric System and Data Analysis

Author : Ted Dunstone
Publisher : Springer Science & Business Media
ISBN 13 : 0387776273
Total Pages : 282 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Biometric System and Data Analysis by : Ted Dunstone

Download or read book Biometric System and Data Analysis written by Ted Dunstone and published by Springer Science & Business Media. This book was released on 2008-10-31 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together aspects of statistics and machine learning to provide a comprehensive guide to evaluating, interpreting and understanding biometric data. It naturally leads to topics including data mining and prediction to be examined in detail. The book places an emphasis on the various performance measures available for biometric systems, what they mean, and when they should and should not be applied. The evaluation techniques are presented rigorously, however they are always accompanied by intuitive explanations. This is important for the increased acceptance of biometrics among non-technical decision makers, and ultimately the general public.

Deep Learning for Biometrics

Author : Bir Bhanu
Publisher : Springer
ISBN 13 : 3319616579
Total Pages : 329 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Deep Learning for Biometrics by : Bir Bhanu

Download or read book Deep Learning for Biometrics written by Bir Bhanu and published by Springer. This book was released on 2017-08-01 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.