Generative Adversarial Networks in Practice, By Mehdi Ghayoumi
Автор: Edited By Roshani Raut, Pranav D Pathak, Sachin R Название: Generative Adversarial Networks and Deep Learning Theory and Applications ISBN: 1032068108 ISBN-13(EAN): 9781032068107 Издательство: Taylor&Francis Рейтинг: Цена: 22968.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications.
Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features:Presents a comprehensive guide on how to use GAN for images and videos.
Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GANHighlights the inclusion of gaming effects using deep learning methodsExamines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutionsThe book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum
Автор: Li Название: Machine Learning Algorithms ISBN: 3031163745 ISBN-13(EAN): 9783031163746 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.
Автор: Partha Niyogi Название: The Informational Complexity of Learning ISBN: 0792380819 ISBN-13(EAN): 9780792380818 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This work seeks to bridge the gap between two learning problems within the same analytical framework. The first concerns the problem of learning functional mappings using neural networks, followed by learning natural language grammars in the principles and parameters tradition of Chomsky.
Artifi cial Intelligence (AI) has been an exciting fi eld of study and research in educational institutions and research labs across the globe. Technology giants and IT organizations invest heavily on AI technologies and tools with the aim of preciselyautomating a variety of simple as well as complicated business operations acrossindustry verticals. This book covers the latest trends and transitions happening in thefuturistic AI domain. The book also focuses on machine and deep learning (ML/DL)algorithms, which are, undoubtedly, the mainstream implementation technologies ofstate-of-the-art AI systems and services. Also, there are chapters on computer vision(CV) and natural language processing (NLP), the primary use cases and applicationsof AI. The book has well-written chapters for demystifying AI model engineeringmethods. Further on, our esteemed readers can fi nd details on AI model evaluation,optimization, deployment and observability. Finally, the book deals and describesgenerative AI, the latest buzzword in the IT industry.
The book
presents the recent ground-breaking changes taking place in the aspects of AI model building, hosting, running and maintaining in cloud environments,
articulates and accentuates the most recent developments taking place in the
domain of Artifi cial Intelligence,
covers the noteworthy innovations and disruptions towards Generative Artifi cial
Intelligence (Generative AI),
explains the breakthrough innovations and disruptions towards Artifi cial General
Intelligence (AGI)
and delineates an engaging discussion of Natural Language Processing, Neuromorphic Systems and Biometrics.
Описание: Focuses on learning vulnerabilities and cyber security. The book gives detail on the new threats and mitigation methods in the cyber security domain, and provides information on the new threats in new technologies such as vulnerabilities in deep learning, data privacy problems with GDPR, and new solutions.
Автор: Vorobeychik, Yevgeniy Kantarcioglu, Murat Название: Adversarial Machine Learning ISBN: 3031004523 ISBN-13(EAN): 9783031004520 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Chen, Pin-yu (research Sta? Member, Ibm Thomas J. Watson Research Center, Yorktown Heights, Ny, Usa) Hsieh, Cho-jui (assistant Professor, Ucla Compute Название: Adversarial robustness for machine learning ISBN: 0128240202 ISBN-13(EAN): 9780128240205 Издательство: Elsevier Science Рейтинг: Цена: 14308.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: He is exactly what this age needs, a real voice of universal spirituality. His appeal is urgent, human and sacred. DAN CRUSEY Sidney, Ohio Each era has its own prophet poets. Russia has been praying and is praying poems by Pushkin, a holy name for every Russian. Ayaz seems to touch us with that sensitivity, inspiring and changing the rhythm of our breathing. SEBARITA KAKHOVSKAYA Ukraine His words transform you through a subtle Alchemy process, and you suddenly travel from a Neophyte to the Connoisseur of Mysteries. His poetry is a gateway to the stars ELLURA ZURIA Rhn, Germany Reading Ayaz is akin to a journey into the
Автор: Hany John, Walters Greg Название: Hands-On Generative Adversarial Networks with PyTorch 1.x ISBN: 1789530512 ISBN-13(EAN): 9781789530513 Издательство: Неизвестно Рейтинг: Цена: 8091.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book will help you understand how GANs architecture works using PyTorch. You will get familiar with the most flexible deep learning toolkit and use it to transform ideas into actual working codes. You will apply GAN models to areas like computer vision, multimedia and natural language processing using a sample-generation perspective.
Автор: Kalin Josh Название: Generative Adversarial Networks Cookbook ISBN: 1789139902 ISBN-13(EAN): 9781789139907 Издательство: Неизвестно Рейтинг: Цена: 9010.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Generative Adversarial Networks have opened up many new possibilities in the machine learning domain. This book is all you need to implement different types of GANs using TensorFlow and Keras, in order to provide optimized and efficient deep learning solutions.
Автор: Mao Xudong, Li Qing Название: Generative Adversarial Networks for Image Generation ISBN: 981336047X ISBN-13(EAN): 9789813360471 Издательство: Springer Цена: 20962.00 р. Наличие на складе: Нет в наличии.
Описание: This book is intended for periodontal residents and practicing periodontists who wish to incorporate the principles of moderate sedation into daily practice. Comprehensive airway management and rescue skills are then documented in detail so that the patient may be properly managed in the event that the sedation progresses beyond the intended level.
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