Deep Learning For Biometrics

Author : Bir Bhanu
Publisher : Springer
ISBN 13 : 3319616579
Total Pages : 312 pages
Book Rating : 4.75/5 ( download)

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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 312 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.

Author : Partha Pratim Sarangi
Publisher : Academic Press
ISBN 13 : 0323903398
Total Pages : 266 pages
Book Rating : 4.94/5 ( download)

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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

Author : Mayank Vatsa
Publisher : CRC Press
ISBN 13 : 1351264982
Total Pages : 254 pages
Book Rating : 4.83/5 ( download)

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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 254 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.

Author : Kisku, Dakshina Ranjan
Publisher : IGI Global
ISBN 13 : 152257526X
Total Pages : 300 pages
Book Rating : 4.69/5 ( download)

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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 300 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.

Author : Gaurav Jaswal
Publisher : CRC Press
ISBN 13 : 1000291669
Total Pages : 409 pages
Book Rating : 4.67/5 ( download)

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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.

Author : Mayank Vatsa
Publisher : CRC Press
ISBN 13 : 1351264990
Total Pages : 316 pages
Book Rating : 4.90/5 ( download)

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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.

Author : Jucheng Yang
Publisher : BoD – Books on Demand
ISBN 13 : 1789235901
Total Pages : 148 pages
Book Rating : 4.06/5 ( download)

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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.

Author : Andrew Jin
Publisher :
ISBN 13 : 9783039366996
Total Pages : 210 pages
Book Rating : 4.98/5 ( download)

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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.

Author : Maria De Marsico
Publisher : Academic Press
ISBN 13 : 0081007124
Total Pages : 248 pages
Book Rating : 4.29/5 ( download)

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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 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book 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

Author : James Eric Mason
Publisher : Springer
ISBN 13 : 3319290886
Total Pages : 223 pages
Book Rating : 4.81/5 ( download)

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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 223 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