Machine learning biometrics (45 risultati)

Condizione: Very Good. Good shape with typical wear. Has a remainder mark. hardcover Used - Very Good 2023.

paperback. Condizione: New. Language:Chinese.Paperback. Pub Date: 2025-01 Publisher: Harbin Engineering University Press.

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Hardback. Condizione: New. Physical Biometrics for Hardware Security of DSP and Machine Learning Coprocessors presents state-of-the art explanations for detective control-based security and protection of digital signal processing (DSP) and machine learning coprocessors against hardware threats. Such threats include intellectual property (IP) abuse and misuse, for example, fraudulent claims of IP ownership and IP piracy. DSP coprocessors such as finite impulse response filters, image processing filters, discrete Fourier transform, and JPEG compression hardware are extensively utilized in several real-life applications. Further, machine learning coprocessors such as convolutional neural network (CNN) hardware IP cores play a vital role in several applications such as face recognition, medical imaging, autonomous driving, and biometric authentication, amongst others. Written by an expert in the field, this book reviews recent advances in hardware security and IP protection of digital signal processing (DSP) and machine learning coprocessors using physical biometrics and DNA. It presents solutions for secured coprocessors for DSP, image processing applications and CNN, and where relevant chapters explores the advantages, disadvantages and security-cost trade-offs between different approaches and techniques to assist in the practical application of these methods. The interdisciplinary themes and topics covered are expected to be of interest to researchers in several areas of specialisation, encompassing the overlapping fields of hardware design security, VLSI design (high level synthesis, register transfer level, gate level synthesis), IP core, optimization using evolutionary computing, system-on-chip design, and biometrics. CAD/design engineers, system architects and students will also find this book to be a useful resource.…

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Condizione: As New. Unread book in perfect condition.

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Condizione: As New. Unread book in perfect condition.

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Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

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Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Hardback. Condizione: New. Physical Biometrics for Hardware Security of DSP and Machine Learning Coprocessors presents state-of-the art explanations for detective control-based security and protection of digital signal processing (DSP) and machine learning coprocessors against hardware threats. Such threats include intellectual property (IP) abuse and misuse, for example, fraudulent claims of IP ownership and IP piracy. DSP coprocessors such as finite impulse response filters, image processing filters, discrete Fourier transform, and JPEG compression hardware are extensively utilized in several real-life applications. Further, machine learning coprocessors such as convolutional neural network (CNN) hardware IP cores play a vital role in several applications such as face recognition, medical imaging, autonomous driving, and biometric authentication, amongst others. Written by an expert in the field, this book reviews recent advances in hardware security and IP protection of digital signal processing (DSP) and machine learning coprocessors using physical biometrics and DNA. It presents solutions for secured coprocessors for DSP, image processing applications and CNN, and where relevant chapters explores the advantages, disadvantages and security-cost trade-offs between different approaches and techniques to assist in the practical application of these methods. The interdisciplinary themes and topics covered are expected to be of interest to researchers in several areas of specialisation, encompassing the overlapping fields of hardware design security, VLSI design (high level synthesis, register transfer level, gate level synthesis), IP core, optimization using evolutionary computing, system-on-chip design, and biometrics. CAD/design engineers, system architects and students will also find this book to be a useful resource.…

Taschenbuch. Condizione: Neu. Machine Learning for Biometrics | Concepts, Algorithms and Applications | Partha Pratim Sarangi (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | Academic Press | EAN 9780323852098 | Verantwortliche Person für die EU: Elsevier B.V., Radarweg 29, 1043 NX AMSTERDAM, NIEDERLANDE, productsafety[at]elsevier[dot]com | Anbieter: preigu. …

Hardcover. Condizione: Brand New. 300 pages. 9.21x6.14x0.98 inches. In Stock.

Condizione: New. 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 perf.

Buch. Condizione: Neu. Neuware - Physical Biometrics for Hardware Security of DSP and Machine Learning Coprocessors presents state-of-the art explanations for detective control-based security and protection of digital signal processing (DSP) and machine learning coprocessors against hardware threats. Such threats include intellectual property (IP) abuse and misuse, for example, fraudulent claims of IP ownership and IP piracy. DSP coprocessors such as finite impulse response filters, image processing filters, discrete Fourier transform, and JPEG compression hardware are extensively utilized in several real-life applications. Further, machine learning coprocessors such as convolutional neural network (CNN) hardware IP cores play a vital role in several applications such as face recognition, medical imaging, autonomous driving, and biometric authentication, amongst others. Written by an expert in the field, this book reviews recent advances in hardware security and IP protection of digital signal processing (DSP) and machine learning coprocessors using physical biometrics and DNA. It presents solutions for secured coprocessors for DSP, image processing applications and CNN, and where relevant chapters explores the advantages, disadvantages and security-cost trade-offs between different approaches and techniques to assist in the practical application of these methods. The interdisciplinary themes and topics covered are expected to be of interest to researchers in several areas of specialisation, encompassing the overlapping fields of hardware design security, VLSI design (high level synthesis, register transfer level, gate level synthesis), IP core, optimization using evolutionary computing, system-on-chip design, and biometrics. CAD/design engineers, system architects and students will also find this book to be a useful resource.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Face recognition has emerged as one of the most significant biometric technologies for automated identification and authentication in modern security, surveillance, and access control systems. Traditional identification methods, such as passwords and identity cards, are increasingly vulnerable to theft, forgery and unauthorized access, thereby necessitating the development of intelligent and reliable biometric solutions. This study presents a machine learning approach to automated face recognition and identification aimed at enhancing the accuracy, efficiency, and robustness of human identity verification systems. The proposed framework employs advanced image preprocessing techniques, including face detection, normalization, feature extraction, and dimensionality reduction to improve the quality and discriminative power of facial data. Machine learning algorithms are utilized to learn distinctive facial features from a large dataset of facial images and subsequently classify individuals based on their unique biometric characteristics. The system is trained and evaluated using benchmark facial image datasets under varying conditions such as illumination changes, facial expressions.…

Taschenbuch. Condizione: Neu. Cybersecurity / Biometrics | A Machine Learning Approach to Automated Face Recognition and Identification | Emmanuel Ogala | Taschenbuch | Englisch | 2026 | GlobeEdit | EAN 9786630194357 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. …

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. Englisch.…