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AI and Deep Learning in Biometric Security

research in the field of AI and biometric security.;

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Deep Biometrics

learning techniques in the emerging new areas such as privacy and security issues, cancellable biometrics, soft biometrics, smart cities, big;

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Deep Biometrics

learning techniques in the emerging new areas such as privacy and security issues, cancellable biometrics, soft biometrics, smart cities, big;

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Hands-On Artificial Intelligence for Cybersecurity

strength of biometric authentication procedures with deep learning Evaluate cybersecurity strategies and learn how you can improve them Who this;

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Deep Learning in Biometrics

biometrics. This book covers topics in deep learning, namely convolutional neural networks, deep belief network and stacked autoencoders. The focus;

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Biometric Security and Privacy: Opportunities & Challenges in the Big Data Era

approaches, and ensemble learning. Included are special biometric technologies related to privacy and security issues, such as cancellable biometrics;

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Biometric Security and Privacy: Opportunities & Challenges in the Big Data Era

approaches, and ensemble learning. Included are special biometric technologies related to privacy and security issues, such as cancellable biometrics;

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Deep Learning for Biometrics

of biometrics security are also examined. Topics and features: addresses the application of deep learning to enhance the performance of biometrics;

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Biometric Authentication in Online Learning Environments

utilizing biometric-based authentication techniques. This book examines e-learning, security, threats in online exams, security considerations, and;

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Artificial Intelligence

From humble evolutions in research papers and labs, artificial intelligence (AI)-which encompasses Machine Learning (ML) and Deep Learning;

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Examining the Impact of Deep Learning and IoT on Multi-Industry Applications

technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving;

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Artificial Intelligence in a Throughput Model: Some Major Algorithms

better results. This has led to growth in the biometrics technology industry, and is set to increase the security and internal control operations;

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Artificial Intelligence in a Throughput Model

better results. This has led to growth in the biometrics technology industry, and is set to increase the security and internal control operations;

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Advanced Deep Learning with Keras

, GANs, VAEs, and deep reinforcement learning that drive today's most impressive AI results. Key Features Explore the most advanced deep;

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Human Recognition in Unconstrained Environments

recognition and machine learning methods for biometric recognition in real-world, real-time settings, especially those related to forensics and;

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Deep Learning in Biomedical and Health Informatics

Provides a proficient guide on the relationship between AI and healthcare and how AI is changing all aspects of the health care industry;

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Artificial Intelligence Technology

learning framework, Huawei MindSpore AI development framework, Huawei Atlas computing platform, Huawei AI open platform for smart terminals, and;

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Deep Learning Approaches to Cloud Security

of its kind to go in-depth on the newest trends and innovations in cloud security through the use of deep learning approaches Covers these;

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Multimodal Biometric Systems

it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system;

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Secure Cryptosystem for Biometric Information Using Rsa

Biometric security will play a central role in the future security system, biometric security is concerned with the assurance;

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Hands-On Artificial Intelligence on Amazon Web Services

introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services;

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AI and Cloud Computing

AI and Cloud Computing, Volume 120 in the Advances in Computers series, highlights new advances in the field, with this updated volume;

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Artificial Intelligence Trends for Data Analytics Using Machine Learning and Deep Learning Approaches

Artificial Intelligence (AI), when incorporated with machine learning and deep learning algorithms, has a wide variety of applications;

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Ascend AI Processor Architecture and Programming

programming technology needed by researchers developing AI applications. Chapters cover the theoretical fundamentals of AI and deep learning;

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Deep Learning and the Game of Go

applying advanced AI techniques, in particular deep learning and reinforcement learning, users can train their Go-bot in the rules and tactics;

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Smart Data

contributions from leading experts and covers cutting-edge topics such as smart data and cloud computing, AI for networking, smart data deep learning;

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Reinforcement Learning

learning, including Markov's Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI before;

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