Products related to Adversarial:
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Generative Adversarial Networks in Practice
This book is an all-inclusive resource that provides a solid foundation on Generative Adversarial Networks (GAN) methodologies, their application to real-world projects, and their underlying mathematical and theoretical concepts. Key Features: Guides you through the complex world of GANs, demystifying their intricacies Accompanies your learning journey with real-world examples and practical applications Navigates the theory behind GANs, presenting it in an accessible and comprehensive way Simplifies the implementation of GANs using popular deep learning platforms Introduces various GAN architectures, giving readers a broad view of their applications Nurture your knowledge of AI with our comprehensive yet accessible content Practice your skills with numerous case studies and coding examples Reviews advanced GANs, such as DCGAN, cGAN, and CycleGAN, with clear explanations and practical examples Adapts to both beginners and experienced practitioners, with content organized to cater to varying levels of familiarity with GANs Connects the dots between GAN theory and practice, providing a well-rounded understanding of the subject Takes you through GAN applications across different data types, highlighting their versatility Inspires the reader to explore beyond this book, fostering an environment conducive to independent learning and research Closes the gap between complex GAN methodologies and their practical implementation, allowing readers to directly apply their knowledge Empowers you with the skills and knowledge needed to confidently use GANs in your projectsPrepare to deep dive into the captivating realm of GANs and experience the power of AI like never before with Generative Adversarial Networks (GANs) in Practice.This book brings together the theory and practical aspects of GANs in a cohesive and accessible manner, making it an essential resource for both beginners and experienced practitioners.
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Adversarial Learning and Secure AI
Providing a logical framework for student learning, this is the first textbook on adversarial learning.It introduces vulnerabilities of deep learning, then demonstrates methods for defending against attacks and making AI generally more robust.To help students connect theory with practice, it explains and evaluates attack-and-defense scenarios alongside real-world examples.Feasible, hands-on student projects, which increase in difficulty throughout the book, give students practical experience and help to improve their Python and PyTorch skills.Book chapters conclude with questions that can be used for classroom discussions.In addition to deep neural networks, students will also learn about logistic regression, naïve Bayes classifiers, and support vector machines.Written for senior undergraduate and first-year graduate courses, the book offers a window into research methods and current challenges.Online resources include lecture slides and image files for instructors, and software for early course projects for students.
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Computer Vision : Object Detection In Adversarial Vision
This comprehensive textbook presents a broad review of both traditional (i.e., conventional) and deep learning aspects of object detection in various adversarial real-world conditions in a clear, insightful, and highly comprehensive style.Beginning with the relation of computer vision and object detection, the text covers the various representation ofobjects, applications of object detection, and real-world challenges faced by the research community for object detection task.The book addresses various real-world degradations and artifacts for the object detection task and also highlights the impacts of artifacts in the object detection problems.The book covers various imaging modalities and benchmark datasets mostly adopted by the research community for solving various aspects of object detection tasks.The book also collects together solutions and perspectives proposed by the preeminent researchers in the field, addressing not only the background of visibility enhancement but also techniques proposed in the literature for visibility enhancement of scenes and detection of objects in various representative real-world challenges. Computer Vision: Object Detection in Adversarial Vision is unique for its diverse content, clear presentation, and overall completeness.It provides a clear, practical, and detailed introduction and advancement of object detection in various representative challenging real-world conditions. Topics and Features:• Offers the first truly comprehensive presentation of aspects of the object detection in degraded and nondegraded environment. • Includes in-depth discussion of various degradation and artifacts, and impact of those artifacts in the real world on solving the object detection problems. • Gives detailed visual examples of applications of object detection in the real world. • Presents a detailed description of popular imaging modalities for object detection adopted by researchers. • Presents the key characteristics of various benchmark datasets in indoor and outdoor environment for solving object detection tasks. • Surveys the complete field of visibility enhancement of degraded scenes, including conventional methods designed for enhancing the degraded scenes as well as the deep architectures. • Discusses techniques for detection of objects in real-world applications. • Contains various hands-on practical examples and a tutorial for solving object detection problems using Python. • Motivates readers to build vision-based systems for solving object detection problems in degraded and nondegraded real-world challenges. The book will be of great interest to a broad audience ranging from researchers and practitioners to graduate and postgraduate students involved in computer vision tasks with respect to object detection in degraded and nondegraded real-world vision problems.
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Raman Scattering on Emerging Semiconductors and Oxides
Raman Scattering on Emerging Semiconductors and Oxides presents Raman scattering studies.It describes the key fundamental elements in applying Raman spectroscopies to various semiconductors and oxides without complicated and deep Raman theories. Across nine chapters, it covers:• SiC and IV-IV semiconductors,• III-GaN and nitride semiconductors,• III-V and II-VI semiconductors,• ZnO-based and GaO-based semiconducting oxides,• Graphene, ferroelectric oxides, and other emerging materials,• Wide-bandgap semiconductors of SiC, GaN, and ZnO, and• Ultra-wide gap semiconductors of AlN, Ga2O3, and graphene. Key achievements from the author and collaborators in the above fields are referred to and cited with typical Raman spectral graphs and analyses.Written for engineers, scientists, and academics, this comprehensive book will be fundamental for newcomers in Raman spectroscopy. Zhe Chuan Feng has had an impressive career spanning many years of important work in engineering and tech, including as a professor at the Graduate Institute of Photonics & Optoelectronics and Department of Electrical Engineering, National Taiwan University, Taipei; establishing the Science Exploring Lab; joining Kennesaw State University as an adjunct professor, part-time; and at the Department of Electrical and Computer Engineering, Southern Polytechnic College of Engineering and Engineering Technology.Currently, he is focusing on materials research for LED, III-nitrides, SiC, ZnO, other semiconductors/oxides, and nanostructures and has devoted time to materials research and growth of III-V and II-VI compounds, LED, III nitrides, SiC, ZnO, GaO, and other semiconductors/oxides. Professor Feng has also edited and published multiple review books in his field, alongside authoring scientific journal papers and conference/proceeding papers.He has organized symposiums and been an invited speaker at different international conferences and universities.He has also served as a guest editor for special journal issues.
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Where has photonics gone?
Photonics has advanced and expanded into various industries and applications, including telecommunications, healthcare, manufacturing, and defense. It has enabled the development of faster and more efficient communication systems, medical imaging technologies, high-precision manufacturing tools, and advanced military equipment. Photonics has also made significant contributions to renewable energy technologies, such as solar cells and LED lighting. Overall, photonics has become an integral part of modern technology and continues to drive innovation in a wide range of fields.
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How advanced is nanotechnology?
Nanotechnology is a rapidly advancing field that involves manipulating materials at the nanoscale, which is on the order of billionths of a meter. It has already led to significant advancements in various industries, including medicine, electronics, and materials science. Researchers are continually developing new techniques and applications for nanotechnology, such as targeted drug delivery, nanoelectronics, and nanomaterials with unique properties. While nanotechnology is still in its early stages, it holds great promise for revolutionizing many aspects of our lives in the future.
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What is NMR spectroscopy?
Nuclear Magnetic Resonance (NMR) spectroscopy is a powerful analytical technique used to study the structure and dynamics of molecules. It provides detailed information about the chemical environment, connectivity, and conformation of atoms within a molecule. By measuring the interactions of atomic nuclei with a magnetic field, NMR spectroscopy can elucidate the molecular structure of organic compounds, proteins, and other biomolecules. This technique is widely used in chemistry, biochemistry, and structural biology for research and drug discovery purposes.
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How is spectroscopy applied?
Spectroscopy is applied in various fields such as chemistry, physics, astronomy, and environmental science. In chemistry, it is used to identify and analyze the chemical composition of substances. In physics, it is used to study the interaction of electromagnetic radiation with matter. In astronomy, it is used to determine the composition, temperature, and motion of celestial objects. In environmental science, it is used to monitor air and water quality by analyzing the presence of pollutants. Overall, spectroscopy is a versatile tool for analyzing the properties of different materials and substances.
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Machine Learning Algorithms : Adversarial Robustness in Signal Processing
This book demonstrates the optimal adversarial attacks against several important signal processing algorithms.Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, the authors reveal the robustness of the signal processing algorithms against adversarial attacks.Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing.Therefore, it is necessary and urgent to investigate the behavior of machine learning algorithms in signal processing under adversarial attacks. The authors in this book mainly examine the adversarial robustness of three commonly used machine learning algorithms in signal processing respectively: linear regression, LASSO-based feature selection, and principal component analysis (PCA).As to linear regression, the authors derive the optimal poisoning data sample and the optimal feature modifications, and also demonstrate the effectiveness of the attack against a wireless distributed learning system.The authors further extend the linear regression to LASSO-based feature selection and study the best strategy to mislead the learning system to select the wrong features.The authors find the optimal attack strategy by solving a bi-level optimization problem and also illustrate how this attack influences array signal processing and weather data analysis.In the end, the authors consider the adversarial robustness of the subspace learning problem.The authors examine the optimal modification strategy under the energy constraints to delude the PCA-based subspace learning algorithm. This book targets researchers working in machine learning, electronic information, and information theory as well as advanced-level students studying these subjects.R&D engineers who are working in machine learning, adversarial machine learning, robust machine learning, and technical consultants working on the security and robustness of machine learning are likely to purchase this book as a reference guide.
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Adversarial Legalism : The American Way of Law, Second Edition
In the first edition of this groundbreaking book, Robert Kagan explained why America is much more adversarial—likely to rely on legal threats and lawsuits—than other economically advanced countries, with more prescriptive laws, more costly adjudications, and more severe penalties.This updated edition also addresses the rise of the conservative legal movement and anti-statism in the Republican party, which have put in sharp relief the virtues of adversarial legalism in its ability to empower citizens, lawyers, and judges to mount challenges to the arbitrary or unlawful exercise of government authority. “This is a wonderful piece of work, richly detailed and beautifully written.It is the best, sanest, and most comprehensive evaluation and critique of the American way of law that I have seen.Every serious scholar concerned with justice and efficiency, and every policymaker who is serious about improving the American legal order, should read this trenchant and exciting book.”—Lawrence Friedman, Stanford University“A tour de force.It is an elegantly written, consistently insightful analysis and critique of the American emphasis on litigation and punitive sanctions in the policy and administrative process.”—Charles R.Epp, Law and Society Review
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Agonistic Democracy and Political Practice : Ways of Being Adversarial
This book explores the implications of agonistic democratic theory for political practice.Fuat Gürsözlü argues that at a time when political parties exacerbate political division, political protesters are characterized as looters and terrorists, and extreme partisanship and authoritarian tendencies are on the rise, the agonistic approach offers a much-needed rethinking of political practice to critically understand challenges to democracy and envision more democratic, inclusive, and peaceful alternatives.Inspired by Chantal Mouffe’s agonistic theory and drawing on insightsof other prominent agonistic scholars, Gürsözlü offers a distinctive approach that develops the connections between the agonistic approach and political practice.His main claim is that approaching democratic politics from an agonistic perspective changes the way we understand the nature of democratic society, the place of political protest in democracy, the nature of adversarial engagement, and the democratic function of political parties.The book also advances an account of agonistic peace that is best fitted to the pluralistic and inherently conflictual nature of democratic societies.This book should be of interest to anyone working in the field of contemporary political theory, political philosophy, peace studies, and philosophy of peace.
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Hearing the Victim : Adversarial Justice, Crime Victims and the State
In recent years far more attention has been paid to victims of crime both in terms of awareness of the effect of crime upon their lives, and in changes that have been made to the criminal justice system to improve their rights and treatment.This process seems set to continue, with legislative plans announced to rebalance the criminal justice system in favour of the victim.This latest book in the Cambridge Criminal Justice Series brings together leading authorities in the field to review the role of the victim in the criminal justice system in the context of these developments.
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Is it possible to create new materials through lower dimensional levels by using femtotechnology instead of nanotechnology?
Femtotechnology operates at the scale of femtometers (10^-15 meters), which is smaller than the scale of nanotechnology (10^-9 meters). At this scale, it is theoretically possible to manipulate individual atomic nuclei and electrons to create entirely new materials with unique properties. By harnessing the power of femtotechnology, scientists may be able to engineer materials with unprecedented strength, conductivity, and other desirable characteristics. However, femtotechnology is still largely theoretical and has not yet been realized in practical applications, so its potential for creating new materials through lower dimensional levels remains speculative.
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Why is Rutherford's scattering experiment called a scattering experiment at all?
Rutherford's experiment is called a scattering experiment because it involved firing alpha particles at a thin gold foil and observing how they scattered after hitting the foil. The term "scattering" refers to the process of particles being deflected from their original path as a result of collisions with the atoms in the foil. By analyzing the pattern of scattering, Rutherford was able to deduce the structure of the atom and propose the existence of a dense, positively charged nucleus at its center. This experiment was crucial in advancing our understanding of atomic structure and the behavior of subatomic particles.
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What are the arguments against nanotechnology?
Some arguments against nanotechnology include concerns about potential health and environmental risks, such as the unknown effects of nanoparticles on living organisms and ecosystems. There are also ethical concerns related to the potential misuse of nanotechnology for military purposes or surveillance. Additionally, there are worries about the unequal distribution of benefits and risks, with some groups potentially being disproportionately affected by the consequences of nanotechnology development.
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What are the dangers of nanotechnology?
The dangers of nanotechnology include potential environmental and health risks. Nanoparticles are so small that they can easily enter the body through inhalation, ingestion, or skin contact, potentially causing harm to human health. There is also concern about the potential for nanoparticles to accumulate in the environment and impact ecosystems. Additionally, the long-term effects of exposure to nanoparticles are not fully understood, raising concerns about their safety. Therefore, it is important to carefully consider the potential risks and benefits of nanotechnology and to regulate its use to minimize potential dangers.
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