Emerging Biometrics: Deep Inference and Other Computational Intelligence

Emerging Biometrics: Deep Inference and Other Computational Intelligence PDF Author: S. Yanushkevich
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 16

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Book Description
This paper aims at identifying emerging computational intelligence trends for the design and modeling of complex biometric-enabled infrastructure and systems. Biometric-enabled systems are evolving towards deep learning and deep inference using the principles of adaptive computing, – the front tides of the modern computational intelligence domain.

Emerging Biometrics: Deep Inference and Other Computational Intelligence

Emerging Biometrics: Deep Inference and Other Computational Intelligence PDF Author: S. Yanushkevich
Publisher: Infinite Study
ISBN:
Category : Mathematics
Languages : en
Pages : 16

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Book Description
This paper aims at identifying emerging computational intelligence trends for the design and modeling of complex biometric-enabled infrastructure and systems. Biometric-enabled systems are evolving towards deep learning and deep inference using the principles of adaptive computing, – the front tides of the modern computational intelligence domain.

AI and Deep Learning in Biometric Security

AI and Deep Learning in Biometric Security PDF Author: Gaurav Jaswal
Publisher: CRC Press
ISBN: 1000291669
Category : Technology & Engineering
Languages : en
Pages : 409

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Book Description
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.

Introduction to Biometrics

Introduction to Biometrics PDF Author: Anil K. Jain
Publisher: Springer
ISBN: 9783031643941
Category : Computers
Languages : en
Pages : 0

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Book Description
This textbook introduces the fundamental concepts and techniques used in biometric recognition to students, practitioners, and non-experts in the field. Specifically, the book describes key methodologies used for sensing, feature extraction, and matching of commonly used biometric modalities such as fingerprint, face, iris, and voice. In addition, it presents techniques for fusion of biometric information to meet stringent accuracy requirements, also discussing various security issues and associated remedies involved in the deployment of biometric systems. Furthermore, this second edition captures the progress made in the field of biometric recognition, with highlights including: Lucid explanation of core biometric concepts (e.g., individuality and persistence), which builds a strong foundation for more in-depth study and research on biometrics A new chapter on deep neural networks that provides a primer to recent advancements in machine learning and computer vision Illustrative examples of how deep neural network models have contributed to the rapid evolution of biometrics in areas such as robust feature representation and synthetic biometric data generation A new chapter on speaker recognition, which introduces the readers to person recognition based on the human voice characteristics Presentation of emerging security threats such as deepfakes and adversarial attacks and sophisticated countermeasures such as presentation attack detection and template security While this textbook has been designed for senior undergraduate students and first-year graduate students studying a course on biometrics, it is also a useful reference guide for biometric system designers, developers, and integrators.

Advances in Biometrics

Advances in Biometrics PDF Author: G.R. Sinha
Publisher: Springer Nature
ISBN: 3030304361
Category : Medical
Languages : en
Pages : 360

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Book Description
This book provides a framework for robust and novel biometric techniques, along with implementation and design strategies. The theory, principles, pragmatic and modern methods, and future directions of biometrics are presented, along with in-depth coverage of biometric applications in driverless cars, automated and AI-based systems, IoT, and wearable devices. Additional coverage includes computer vision and pattern recognition, cybersecurity, cognitive computing, soft biometrics, and the social impact of biometric technology. The book will be a valuable reference for researchers, faculty, and practicing professionals working in biometrics and related fields, such as image processing, computer vision, and artificial intelligence. Highlights robust and novel biometrics techniques Provides implementation strategies and future research directions in the field of biometrics Includes case studies and emerging applications

Deep Biometrics

Deep Biometrics PDF Author: Richard Jiang
Publisher: Springer Nature
ISBN: 3030325830
Category : Technology & Engineering
Languages : en
Pages : 322

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Book Description
This book highlights new advances in biometrics using deep learning toward deeper and wider background, deeming it “Deep Biometrics”. The book aims to highlight recent developments in biometrics using semi-supervised and unsupervised methods such as Deep Neural Networks, Deep Stacked Autoencoder, Convolutional Neural Networks, Generative Adversary Networks, and so on. The contributors demonstrate the power of deep learning techniques in the emerging new areas such as privacy and security issues, cancellable biometrics, soft biometrics, smart cities, big biometric data, biometric banking, medical biometrics, healthcare biometrics, and biometric genetics, etc. The goal of this volume is to summarize the recent advances in using Deep Learning in the area of biometric security and privacy toward deeper and wider applications. Highlights the impact of deep learning over the field of biometrics in a wide area; Exploits the deeper and wider background of biometrics, such as privacy versus security, biometric big data, biometric genetics, and biometric diagnosis, etc.; Introduces new biometric applications such as biometric banking, internet of things, cloud computing, and medical biometrics.

Biometrics

Biometrics PDF Author: N. V. Boulgouris
Publisher: John Wiley & Sons
ISBN: 0470522348
Category : Computers
Languages : en
Pages : 763

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Book Description
Edited by a panel of experts, this book fills a gap in the existing literature by comprehensively covering system, processing, and application aspects of biometrics, based on a wide variety of biometric traits. The book provides an extensive survey of biometrics theory, methods,and applications, making it an indispensable source of information for researchers, security experts, policy makers, engineers, practitioners, and graduate students. The book's wide and in-depth coverage of biometrics enables readers to build a strong, fundamental understanding of theory and methods, and provides a foundation for solutions to many of today’s most interesting and challenging biometric problems. Biometric traits covered: Face, Fingerprint, Iris, Gait, Hand Geometry, Signature, Electrocardiogram (ECG), Electroencephalogram (EEG), physiological biometrics. Theory, Methods and Applications covered: Multilinear Discriminant Analysis, Neural Networks for biometrics, classifier design, biometric fusion, Event-Related Potentials, person-specific characteristic feature selection, image and video-based face, recognition/verification, near-infrared face recognition, elastic graph matching, super-resolution of facial images, multimodal solutions, 3D approaches to biometrics, facial aging models for recognition, information theory approaches to biometrics, biologically-inspired methods, biometric encryption, decision-making support in biometric systems, privacy in biometrics.

Machine Learning for Biometrics

Machine Learning for Biometrics PDF Author: Partha Pratim Sarangi
Publisher: Academic Press
ISBN: 0323903398
Category : Computers
Languages : en
Pages : 266

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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

Intelligent Biometric Techniques in Fingerprint and Face Recognition

Intelligent Biometric Techniques in Fingerprint and Face Recognition PDF Author: Lakhmi C. Jain
Publisher: CRC Press
ISBN: 9780849320552
Category : Technology & Engineering
Languages : en
Pages : 478

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Book Description
The tremendous world-wide interest in intelligent biometric techniques in fingerprint and face recognition is fueled by the myriad of potential applications, including banking and security systems, and limited only by the imaginations of scientists and engineers. This growing interest poses new challenges to the fields of expert systems, neural networks, fuzzy systems, and evolutionary computing, which offer the advantages of learning abilities and human-like behavior. Biometric Techniques in Fingerprint and Face Recognition presents a thorough treatment of established and emerging applications and techniques relevant to this field so rich with opportunity.

Soft Computing for Recognition Based on Biometrics

Soft Computing for Recognition Based on Biometrics PDF Author: Patricia Melin
Publisher: Springer Science & Business Media
ISBN: 3642151108
Category : Computers
Languages : en
Pages : 449

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Book Description
This book describes bio-inspired models and applications of hybrid intelligent systems using soft computing techniques for image analysis and pattern recognition based on biometrics and other sources. Each section groups papers on a similar subject.

Deep Learning in Biometrics

Deep Learning in Biometrics PDF Author: Mayank Vatsa
Publisher: CRC Press
ISBN: 1351264990
Category : Computers
Languages : en
Pages : 316

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Book Description
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.