Understanding Artificial Intelligence, Ralf T. Kreutzer; Marie Sirrenberg
Автор: Millington, Ian, Funge, John Название: Artificial Intelligence for Games ISBN: 0123747317 ISBN-13(EAN): 9780123747310 Издательство: Taylor&Francis Рейтинг: Цена: 72470.00 T Наличие на складе: Поставка под заказ. Описание: Creating robust artificial intelligence is one of the greatest challenges for game developers, yet the commercial success of a game is often dependent upon the quality of the AI. In this book, Ian Millington brings extensive professional experience to the problem of improving the quality of AI in games. He describes numerous examples from real games and explores the underlying ideas through detailed case studies. He goes further to introduce many techniques little used by developers today. The book's associated web site contains a library of C++ source code and demonstration programs, and a complete commercial source code library of AI algorithms and techniques.<br><br>"Artificial Intelligence for Games - 2nd edition" will be highly useful to academics teaching courses on game AI, in that it includes exercises with each chapter. It will also include new and expanded coverage of the following: AI-oriented gameplay; Behavior driven AI; Casual games (puzzle games). <br><br>* The first comprehensive, professional tutorial and reference to implement true AI in games written by an engineer with extensive industry experience.<br>* Walks through the entire development process from beginning to end.<br>* Includes examples from over 100 real games, 10 in-depth case studies, and web site with sample code.
Автор: George, Michael L., Название: Lean six sigma in the age of artificial intelligence : ISBN: 1260135039 ISBN-13(EAN): 9781260135039 Издательство: McGraw-Hill Рейтинг: Цена: 35450.00 T Наличие на складе: Поставка под заказ. Описание: The world's leading expert on Lean Six Sigma provides the missing link for reducing waste and taking operations to the next level: Artificial IntelligenceLean Six Sigma (LSS) has been helping companies improve their processes since 2001-but as yet, no one has taken this revolutionary management approach to its limits. Now, The Fourth Revolution in Manufacturing shows exactly how to do that-by adding artificial intelligence (AI) to the mix. This game-changing guide takes you through the process of using AI to unlock maximum speed, solve complex manufacturing challenges, reduce waste, increase company profits, and ultimately beat the competition.
Breakthrough Manufacturing explains how to:* Unlock your company's full potential with the AI + LSS approach* Utilize the AI + LSS three-step process to dramatically improve profits * Apply AI + LSS to engineering and other non-manufacturing processes* Harness the interaction of AI+LSS and the ERP system* Create a scorecard and measure your results
Learn how Artificial Intelligence (AI) is being applied in the fashion industry. With an application focused approach, this book provides real-world examples, breaks down technical jargon for non-technical readers, and provides an educational resource for fashion professionals. The book investigates the ways in which AI is impacting every part of the fashion value chain starting with product discovery and working backwards to manufacturing.
Artificial Intelligence for Fashion walks you through concepts, such as connected retail, data mining, and artificially intelligent robotics. Each chapter contains an example of how AI is being applied in the fashion industry illustrated by one major technological theme. There are no equations, algorithms, or code. The technological explanations are cumulative so you'll discover more information about the inner workings of artificial intelligence in practical stages as the book progresses.
What You'll Learn
Gain a basic understanding of AI and how it is used in fashion
Understand key terminology and concepts in AI
Review the new competitive landscape of the fashion industry
Conceptualize and develop new ways to apply AI within the workplace
Who This Book Is For Fashion industry professionals from designers, managers, department heads, and executives can use this book to learn about how AI is impacting roles in every department and profession.
Автор: Lawless, William Название: Artificial Intelligence for the Internet of Everything ISBN: 0128176369 ISBN-13(EAN): 9780128176368 Издательство: Elsevier Science Рейтинг: Цена: 110030.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Artificial Intelligence for the Internet of Everything considers the foundations, metrics and applications of IoE systems. It covers whether devices and IoE systems should speak only to each other, to humans or to both. Further, the book explores how IoE systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems. It examines the meaning, value and effect that IoT has had and may have on ordinary life, in business, on the battlefield, and with the rise of intelligent and autonomous systems. Based on an artificial intelligence (AI) perspective, this book addresses how IoE affects sensing, perception, cognition and behavior.
Each chapter addresses practical, measurement, theoretical and research questions about how these "things" may affect individuals, teams, society or each other. Of particular focus is what may happen when these "things" begin to reason, communicate and act autonomously on their own, whether independently or interdependently with other "things."
Considers the foundations, metrics and applications of IoE systems
Debates whether IoE systems should speak to humans and each other
Explores how IoE systems affect targeted audiences and society
Discusses theoretical IoT ecosystem models
Автор: George Binto, Carmichael Gail Название: Artificial Intelligence Simplified: Understanding Basic Concepts ISBN: 1944708006 ISBN-13(EAN): 9781944708009 Издательство: Неизвестно Цена: 22980.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
A small book that introduces key Artificial Intelligence (AI) concepts in an easy-to-read format with examples and illustrations. A complex, long, overly mathematical textbook does not always serve the purpose of conveying the basic AI concepts to most people. Someone with basic knowledge in Computer Science can have a quick overview of AI (heuristic searches, genetic algorithms, expert systems, game trees, fuzzy expert systems, natural language processing, super intelligence, etc.) with everyday examples. If you are taking a basic AI course and find the traditional AI textbooks intimidating, you may choose this as a "bridge" book, or as an introductory textbook. (This is old edition -- a new revised edition is currently available.)
Автор: Nie Liqiang, Liu Meng, Song Xuemeng Название: Multimodal Learning toward Micro-Video Understanding ISBN: 1681736284 ISBN-13(EAN): 9781681736280 Издательство: Mare Nostrum (Eurospan) Цена: 82230.00 T Наличие на складе: Нет в наличии. Описание:
Micro-videos, a new form of user-generated content, have been spreading widely across various social platforms, such as Vine, Kuaishou, and TikTok.
Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to their brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for high-order micro-video understanding.
Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of venue categories to guide micro-video analysis; (3) how to alleviate the influence of low quality caused by complex surrounding environments and camera shake; (4) how to model multimodal sequential data, i.e. textual, acoustic, visual, and social modalities to enhance micro-video understanding; and (5) how to construct large-scale benchmark datasets for analysis. These challenges have been largely unexplored to date.
In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.
Автор: Nie Liqiang, Liu Meng, Song Xuemeng Название: Multimodal Learning toward Micro-Video Understanding ISBN: 1681736306 ISBN-13(EAN): 9781681736303 Издательство: Mare Nostrum (Eurospan) Цена: 103490.00 T Наличие на складе: Нет в наличии. Описание:
Micro-videos, a new form of user-generated content, have been spreading widely across various social platforms, such as Vine, Kuaishou, and TikTok.
Different from traditional long videos, micro-videos are usually recorded by smart mobile devices at any place within a few seconds. Due to their brevity and low bandwidth cost, micro-videos are gaining increasing user enthusiasm. The blossoming of micro-videos opens the door to the possibility of many promising applications, ranging from network content caching to online advertising. Thus, it is highly desirable to develop an effective scheme for high-order micro-video understanding.
Micro-video understanding is, however, non-trivial due to the following challenges: (1) how to represent micro-videos that only convey one or few high-level themes or concepts; (2) how to utilize the hierarchical structure of venue categories to guide micro-video analysis; (3) how to alleviate the influence of low quality caused by complex surrounding environments and camera shake; (4) how to model multimodal sequential data, i.e. textual, acoustic, visual, and social modalities to enhance micro-video understanding; and (5) how to construct large-scale benchmark datasets for analysis. These challenges have been largely unexplored to date.
In this book, we focus on addressing the challenges presented above by proposing some state-of-the-art multimodal learning theories. To demonstrate the effectiveness of these models, we apply them to three practical tasks of micro-video understanding: popularity prediction, venue category estimation, and micro-video routing. Particularly, we first build three large-scale real-world micro-video datasets for these practical tasks. We then present a multimodal transductive learning framework for micro-video popularity prediction. Furthermore, we introduce several multimodal cooperative learning approaches and a multimodal transfer learning scheme for micro-video venue category estimation. Meanwhile, we develop a multimodal sequential learning approach for micro-video recommendation. Finally, we conclude the book and figure out the future research directions in multimodal learning toward micro-video understanding.
Автор: Danel Jaso Название: Robust Speech Recognition and Understanding ISBN: 1681174669 ISBN-13(EAN): 9781681174662 Издательство: Gazelle Book Services Рейтинг: Цена: 217350.00 T Наличие на складе: Невозможна поставка. Описание: "Speech recognition systems have become much more robust in recent years with respect to both speaker variability and acoustical variability. Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems. In addition to achieving speaker independence, many current systems can also automatically compensate for modest amounts of acoustical degradation caused by the effects of unknown noise and unknown linear filtering. As speech recognition and spoken language technologies are being transferred to real applications, the need for greater robustness in recognition technology is becoming increasingly apparent. Substantial progress has also been made over the last decade in the dynamic adaptation of speech recognition systems to new speakers, with techniques that modify or warp the systems phonetic representations to reflect the acoustical characteristics of individual speakers. Speech recognition systems have also become more robust in recent years, particularly with regard to slowly-varying acoustical sources of degradation. As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. Robust Speech Recognition and Understanding brings together many different aspects of the current research on automatic speech recognition and language understanding. Additionally, it presents a comprehensive survey of the state-ofthe-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences. "
Автор: Amal Kumar Adak Название: Emerging Research on Applied Fuzzy Sets and Intuitionistic Fuzzy Matrices ISBN: 1522509143 ISBN-13(EAN): 9781522509141 Издательство: Turpin Рейтинг: Цена: 199950.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The use of fuzzy logic has become prominent in a variety of fields and applications. By implementing these logic sets, problems and uncertainties are more effectively resolved.Emerging Research on Applied Fuzzy Sets and Intuitionistic Fuzzy Matrices is a pivotal reference source for the latest scholarly perspectives on the interdisciplinary use of fuzzy logic theory, focusing on the application of sets and matrices. Highlighting theoretical framework and empirical research findings, this book is ideally designed for academics, practitioners, upper-level students, and professionals interested in an innovative overview of fuzzy logic sets and matrices.
Автор: Walter J. Scheirer Название: Extreme Value Theory-Based Methods for Visual Recognition ISBN: 1627057005 ISBN-13(EAN): 9781627057004 Издательство: Turpin Рейтинг: Цена: 68930.00 T Наличие на складе: Невозможна поставка. Описание: A common feature of many approaches to modeling sensory statistics is an emphasis on capturing the ""average."" From early representations in the brain, to highly abstracted class categories in machine learning for classification tasks, central-tendency models based on the Gaussian distribution are a seemingly natural and obvious choice for modeling sensory data. However, insights from neuroscience, psychology, and computer vision suggest an alternate strategy: preferentially focusing representational resources on the extremes of the distribution of sensory inputs. The notion of treating extrema near a decision boundary as features is not necessarily new, but a comprehensive statistical theory of recognition based on extrema is only now just emerging in the computer vision literature. This book begins by introducing the statistical Extreme Value Theory (EVT) for visual recognition. In contrast to central-tendency modeling, it is hypothesized that distributions near decision boundaries form a more powerful model for recognition tasks by focusing coding resources on data that are arguably the most diagnostic features. EVT has several important properties: strong statistical grounding, better modeling accuracy near decision boundaries than Gaussian modeling, the ability to model asymmetric decision boundaries, and accurate prediction of the probability of an event beyond our experience. The second part of the book uses the theory to describe a new class of machine learning algorithms for decision making that are a measurable advance beyond the state-of-the-art. This includes methods for post-recognition score analysis, information fusion, multi-attribute spaces, and calibration of supervised machine learning algorithms.
Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity and smart autonomous search engines. The book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. The success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel and Amazon can be interpreted using this book.
Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN)
Authored by top experts, global field pioneers and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making
Edited by high-level academics and researchers in intelligent systems and neural networks
Автор: Saifullah Khalid Название: Applied computational intelligence and soft computing in engineering / ISBN: 1522531297 ISBN-13(EAN): 9781522531296 Издательство: Turpin Рейтинг: Цена: 252560.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Although computational intelligence and soft computing are both well-known fields, using computational intelligence and soft computing in conjunction is an emerging concept. This combination can effectively be used in practical areas of various fields of research. Applied Computational Intelligence and Soft Computing in Engineering is an essential reference work featuring the latest scholarly research on the concepts, paradigms, and algorithms of computational intelligence and its constituent methodologies such as evolutionary computation, neural networks, and fuzzy logic. Including coverage on a broad range of topics and perspectives such as cloud computing, sampling in optimization, and swarm intelligence, this publication is ideally designed for engineers, academicians, technology developers, researchers, and students seeking current research on the benefits of applying computation intelligence techniques to engineering and technology.
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