Information Storage, Cornelia S. Gro?e; Rolf Drechsler
Автор: Rees Название: Physical Principles of Remote Sensing (2017) ISBN: 052118116X ISBN-13(EAN): 9780521181167 Издательство: Cambridge Academ Рейтинг: Цена: 6599.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Covering a wide range of remote sensing techniques and applications, this new edition is now more accessible to students, while retaining its focus on physical and mathematical principles. Chapter summaries, review questions, problem sets and supporting online material allow students to test their understanding and practise handling data for themselves.
Автор: MALLICK & BORAH Название: Emerging Trends and Applications in Cognitive Computing ISBN: 1522557938 ISBN-13(EAN): 9781522557937 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 26961.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Though an individual can process a limitless amount of information, the human brain can only comprehend a small amount of data at a time. Using technology can improve the process and comprehension of information, but the technology must learn to behave more like a human brain to employ concepts like memory, learning, visualization ability, and decision making.Emerging Trends and Applications in Cognitive Computing is a fundamental scholarly source that provides empirical studies and theoretical analysis to show how learning methods can solve important application problems throughout various industries and explain how machine learning research is conducted. Including innovative research on topics such as deep neural networks, cyber-physical systems, and pattern recognition, this collection of research will benefit individuals such as IT professionals, academicians, students, researchers, and managers.
Автор: Omar Alonso Название: The Practice of Crowdsourcing ISBN: 1681735253 ISBN-13(EAN): 9781681735252 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 13999.00 р. Наличие на складе: Нет в наличии.
Описание: Many data-intensive applications that use machine learning or artificial intelligence techniques depend on humans providing the initial dataset, enabling algorithms to process the rest or for other humans to evaluate the performance of such algorithms. Not only can labeled data for training and evaluation be collected faster, cheaper, and easier than ever before, but we now see the emergence of hybrid human-machine software that combines computations performed by humans and machines in conjunction. There are, however, real-world practical issues with the adoption of human computation and crowdsourcing. Building systems and data processing pipelines that require crowd computing remains difficult. In this book, we present practical considerations for designing and implementing tasks that require the use of humans and machines in combination with the goal of producing high-quality labels.
Описание: This book presents a contemporary view of the role of information quality in information fusion and decision making, and provides a formal foundation and the implementation strategies required for dealing with insufficient information quality in building fusion systems for decision making.
Описание: This book introduces quantitative intertextuality, a new approach to the algorithmic study of information reuse in text, sound and images. Employing a variety of tools from machine learning, natural language processing, and computer vision, readers will learn to trace patterns of reuse across diverse sources for scholarly work and practical applications. The respective chapters share highly novel methodological insights in order to guide the reader through the basics of intertextuality.
In Part 1, "Theory", the theoretical aspects of intertextuality are introduced, leading to a discussion of how they can be embodied by quantitative methods. In Part 2, "Practice", specific quantitative methods are described to establish a set of automated procedures for the practice of quantitative intertextuality. Each chapter in Part 2 begins with a general introduction to a major concept (e.g., lexical matching, sound matching, semantic matching), followed by a case study (e.g., detecting allusions to a popular television show in tweets, quantifying sound reuse in Romantic poetry, identifying influences in fan faction by thematic matching), and finally the development of an algorithm that can be used to reveal parallels in the relevant contexts.
Because this book is intended as a "gentle" introduction, the emphasis is often on simple yet effective algorithms for a given matching task. A set of exercises is included at the end of each chapter, giving readers the chance to explore more cutting-edge solutions and novel aspects to the material at hand. Additionally, the book's companion website includes software (R and C++ library code) and all of the source data for the examples in the book, as well as supplemental content (slides, high-resolution images, additional results) that may prove helpful for exploring the different facets of quantitative intertextuality that are presented in each chapter.
Given its interdisciplinary nature, the book will appeal to a broad audience. From practitioners specializing in forensics to students of cultural studies, readers with diverse backgrounds (e.g., in the social sciences, natural language processing, or computer vision) will find valuable insights.
Автор: Lu Zhe-Ming Название: Lossless Information Hiding in Images ISBN: 0128120061 ISBN-13(EAN): 9780128120064 Издательство: Elsevier Science Рейтинг: Цена: 8083.00 р. Наличие на складе: Поставка под заказ.
Описание:
Lossless Information Hiding in Images introduces many state-of-the-art lossless hiding schemes, most of which come from the authors' publications in the past five years. After reading this book, readers will be able to immediately grasp the status, the typical algorithms, and the trend of the field of lossless information hiding.
Lossless information hiding is a technique that enables images to be authenticated and then restored to their original forms by removing the watermark and replacing overridden images. This book focuses on the lossless information hiding in our most popular media, images, classifying them in three categories, i.e., spatial domain based, transform domain based, and compressed domain based. Furthermore, the compressed domain based methods are classified into VQ based, BTC based, and JPEG/JPEG2000 based.
Focuses specifically on lossless information hiding for images
Covers the most common visual medium, images, and the most common compression schemes, JPEG and JPEG 2000
Includes recent state-of-the-art techniques in the field of lossless image watermarking
Presents many lossless hiding schemes, most of which come from the authors' publications in the past five years
Автор: Dornberger Название: Business Information Systems and Technology 4.0 ISBN: 331974321X ISBN-13(EAN): 9783319743219 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses digitalization trends and their concrete applications in business and societal contexts. As such, it addresses the needs of both professors and researchers, who are constantly seeking inspiration, and of managers seeking to tap the potential of the latest trends to take their business to the next level.
Автор: Kenneth C.C. Yang Название: Cases on Immersive Virtual Reality Techniques ISBN: 1522559124 ISBN-13(EAN): 9781522559122 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 31462.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: As virtual reality approaches mainstream consumer use, new research and innovations in the field have impacted how we view and can use this technology across a wide range of industries. Advancements in this technology have led to recent breakthroughs in sound, perception, and visual processing that take virtual reality to new dimensions. As such, research is needed to support the adoption of these new methods and applications. Cases on Immersive Virtual Reality Techniques is an essential reference source that discusses new applications of virtual reality and how they can be integrated with immersive techniques and computer resources. Featuring research on topics such as 3D modeling, cognitive load, and motion cueing, this book is ideally designed for educators, academicians, researchers, and students seeking coverage on the applications of collaborative virtual environments.
Автор: Isao Orishimo; Geoffrey J.D. Hewings; Peter Nijkam Название: Information Technology: Social and Spatial Perspectives ISBN: 3540501584 ISBN-13(EAN): 9783540501589 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book contains perspectives on the way new informationtechnology might reorient the spatial organization ofactivity. Considerable debate is focused on therole of distance and the way in which new informationtechnology might re-shape interaction and, eventually, theform and function of urban areas.
Автор: Amihai Motro; Philippe Smets Название: Uncertainty Management in Information Systems ISBN: 0792398033 ISBN-13(EAN): 9780792398035 Издательство: Springer Рейтинг: Цена: 32004.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Describes how information systems can be made to manage information permeated with uncertainty. This book describes issues and challenges in the area of imperfect information that confront information systems. It covers the principal theories for modeling imperfect information, and shows how these theories may be adapted to information systems.
Автор: Eunikka Mercier-Laurent; David Leake Название: Intelligent Information Processing IV ISBN: 0387876847 ISBN-13(EAN): 9780387876849 Издательство: Springer Рейтинг: Цена: 18161.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 5th IFIP International Conference on Intelligent Information Processing held in Beijing, China on October 19-22, 2008. This work covers topics including: foundations of computer science; software theory and practice; education; communication systems; information systems; and, computer systems technology.
Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics ISBN: 179981193X ISBN-13(EAN): 9781799811930 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 27027.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
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