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Deep Learning-Based Face Analytics

2021-08-16 Computers
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Release : 2021-08-16
Genre : Computers
Kind : eBook
Book Rating : 976/5 ( reviews)

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Book Synopsis Deep Learning-Based Face Analytics by : Nalini K Ratha

Download or read book Deep Learning-Based Face Analytics written by Nalini K Ratha. This book was released on 2021-08-16. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field. Even though there have been a number of different approaches proposed in the literature for face recognition based on deep learning methods, there is not a single book available in the literature that gives a complete overview of these methods. The proposed book captures the state of the art in face recognition using various deep learning methods, and it covers a variety of different topics related to face recognition. This book is aimed at graduate students studying electrical engineering and/or computer science. Biometrics is a course that is widely offered at both undergraduate and graduate levels at many institutions around the world: This book can be used as a textbook for teaching topics related to face recognition. In addition, the work is beneficial to practitioners in industry who are working on biometrics-related problems. The prerequisites for optimal use are the basic knowledge of pattern recognition, machine learning, probability theory, and linear algebra.

Deep Learning in Biometrics

2018-03-05 Computers
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Release : 2018-03-05
Genre : Computers
Kind : eBook
Book Rating : 990/5 ( reviews)

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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. This book was released on 2018-03-05. 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 Techniques for Multimedia

2008-02-07 Computers
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Release : 2008-02-07
Genre : Computers
Kind : eBook
Book Rating : 718/5 ( reviews)

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Book Synopsis Machine Learning Techniques for Multimedia by : Matthieu Cord

Download or read book Machine Learning Techniques for Multimedia written by Matthieu Cord. This book was released on 2008-02-07. Available in PDF, EPUB and Kindle. Book excerpt: Processing multimedia content has emerged as a key area for the application of machine learning techniques, where the objectives are to provide insight into the domain from which the data is drawn, and to organize that data and improve the performance of the processes manipulating it. Arising from the EU MUSCLE network, this multidisciplinary book provides a comprehensive coverage of the most important machine learning techniques used and their application in this domain.

Handbook of Biometric Anti-Spoofing

2019-01-01 Computers
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Release : 2019-01-01
Genre : Computers
Kind : eBook
Book Rating : 276/5 ( reviews)

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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. This book was released on 2019-01-01. 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.

Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments

2020-12-25 Computers
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Release : 2020-12-25
Genre : Computers
Kind : eBook
Book Rating : 920/5 ( reviews)

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Book Synopsis Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments by : Raj, Alex Noel Joseph

Download or read book Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments written by Raj, Alex Noel Joseph. This book was released on 2020-12-25. Available in PDF, EPUB and Kindle. Book excerpt: Recent advancements in imaging techniques and image analysis has broadened the horizons for their applications in various domains. Image analysis has become an influential technique in medical image analysis, optical character recognition, geology, remote sensing, and more. However, analysis of images under constrained and unconstrained environments require efficient representation of the data and complex models for accurate interpretation and classification of data. Deep learning methods, with their hierarchical/multilayered architecture, allow the systems to learn complex mathematical models to provide improved performance in the required task. The Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments provides a critical examination of the latest advancements, developments, methods, systems, futuristic approaches, and algorithms for image analysis and addresses its challenges. Highlighting concepts, methods, and tools including convolutional neural networks, edge enhancement, image segmentation, machine learning, and image processing, the book is an essential and comprehensive reference work for engineers, academicians, researchers, and students.

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