Discriminative Learning In Biometrics

Author : David Zhang
Publisher : Springer
ISBN 13 : 9811020566
Total Pages : 266 pages
Book Rating : 4.68/5 ( download)

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Download or read book Discriminative Learning in Biometrics written by David Zhang and published by Springer. This book was released on 2016-10-26 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph describes the latest advances in discriminative learning methods for biometric recognition. Specifically, it focuses on three representative categories of methods: sparse representation-based classification, metric learning, and discriminative feature representation, together with their applications in palmprint authentication, face recognition and multi-biometrics. The ideas, algorithms, experimental evaluation and underlying rationales are also provided for a better understanding of these methods. Lastly, it discusses several promising research directions in the field of discriminative biometric recognition.

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 : David Zhang
Publisher : IGI Global
ISBN 13 : 159140830X
Total Pages : 375 pages
Book Rating : 4.07/5 ( download)

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Download or read book Biometric Image Discrimination Technologies written by David Zhang and published by IGI Global. This book was released on 2006-01-01 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The book gives an introduction to basic biometric image discrimination technologies including theories that are the foundations of those technologies and new algorithms for biometrics authentication"--Provided by publisher.

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 : Sun Yuan Kung
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 504 pages
Book Rating : 4.74/5 ( download)

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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

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 : Gaurav Jaswal
Publisher : CRC Press
ISBN 13 : 1000291626
Total Pages : 378 pages
Book Rating : 4.29/5 ( 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 2021-03-21 with total page 378 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 : 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 : Andrew Teoh Beng Jin
Publisher : MDPI
ISBN 13 : 303936698X
Total Pages : 210 pages
Book Rating : 4.89/5 ( download)

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Download or read book Advanced Biometrics with Deep Learning written by Andrew Teoh Beng Jin and published by MDPI. This book was released on 2020-12-28 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.