تحسين النتائح
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الى
الصفحة 4
الصفحة 4
Artificial intelligence for multimedia signal processing
Artificial intelligence technologies are also actively applied to broadcasting and multimedia processing technologies. A lot of research has been conducted in a wide variety of fields, such as content creation, transmission, and security, and these attempts have been made in the past two to three years to improve image, video, speech, and other data compression efficiency in areas related to MPEG media processing technology. Additionally, technologies such as media creation, processing, editing, and creating scenarios are very important areas of research in multimedia processing and engineering. This book contains a collection of some topics broadly across advanced computational intelligence algorithms and technologies for emerging multimedia signal processing as: Computer vision field, speech/sound/text processing, and content analysis/information mining.
Artificial intelligence applied to medical imaging and computational biology
Medical imaging and computational biology continuously pose new fundamental medical and biological questions that often give rise to novel challenges in Artificial Intelligence. These research fields present an increasing need for the application of cutting-edge computational approaches that generally involve machine learning or computational intelligence techniques, which can effectively perform bioimage and biosignal processing in different clinical areas.
Artificial Intelligence Applications for Health Care
Covers topics on health care and artificial intelligence. Data sets related to biomedical signals (ECG, EEG, EMG) and images (X-rays, MRI, CT) are explored, analyzed, and processed through different computation intelligence methods. Applications of computational intelligence techniques like artificial and deep neural networks, swarm optimization, expert systems, decision support systems, clustering, and classification techniques on medial datasets are explained. Survey of medical signals, medial images, and computation intelligence methods are also provided.
Artificial Intelligence : Applications and innovations
It's about the science of artificial intelligence (AI). AI is the study of the design of intelligent computational agents. This book provides a valuable resource for researchers, scientists, professionals, academicians and students dealing with the new challenges and advances in the areas of AI and innovations. This book also covers a wide range of applications of machine learning such as fire detection, structural health and pollution monitoring and control. Provides insight into prospective research and application areas related to industry and technology / Discusses industry- based inputs on success stories of technology adoption / Discusses technology applications from a research perspective in the field of AI / Provides a hands- on approach and case studies for readers of the book to practice and assimilate learning
Architecture of computing systems - ARCS 2008 ; 21st International Conference, Dresden, Germany, February 25-28, 2008. Proceedings
This book constitutes the refereed proceedings of the 21st International Conference on Architecture of Computing Systems, ARCS 2008, held in Dresden, Germany, in February 2008.
Architecture of advanced numerical analysis systems: designing a scientific computing system using ocaml
Applies the functional OCaml programming language to numerical or computational weighted data science, engineering, and scientific applications. This book is based on the authors' first-hand experience building and maintaining Owl, an OCaml-based numerical computing library. You'll first learn the various components in a modern numerical computation library. Then, you will learn how these components are designed and built up and how to optimize their performance. After reading and using this book, you'll have the knowledge required to design and build real-world complex systems that effectively leverage the advantages of the OCaml functional programming language.
Applied mathematics and machine learning
The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications.
Applied and computational mathematics for digital environments
Contains the 11 papers that were accepted and published in the Special Issue “Applied and Computational Mathematics for Digital Environments” of the MDPI Mathematics journal. The topics of interest include, among others, scientific research, applied tasks, and problems in the following areas: The construction of mathematical and information models of intelligent computer systems for monitoring and controlling the parameters of digital environments; The development of intelligent optimization algorithms that search for optimal parameter values of mathematical and information models in digital environments; Software and mathematical technologies in the implementation of intelligent monitoring and computer control of the parameters of digital environments; The development and application of mathematical and information models, machine learning methods, and artificial intelligence for the analysis and processing of big data in digital environments.
Applications of evolutionary computing ; EvoWorkshops 2008 : EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog, Naples, Italy, March 26-28, 2008. Proceedings
This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and should help and - spire researchers and professionals to develop e?cient EC methods for design and problem solving.
Applications of computational intelligence
Computational intelligence (CI) is the theory, design, application, and development of biologically and linguistically motivated computational paradigms. Traditionally, the three main pillars of CI have been neural networks, fuzzy systems, and evolutionary computation. However, in time, many nature-inspired computing paradigms have evolved. Thus, CI is an evolving field, and, at present, in addition to the three main constituents, it encompasses computing paradigms such as ambient intelligence, artificial life, cultural learning, artificial endocrine networks, social reasoning, and artificial hormone networks. CI plays a major role in developing successful intelligent systems, including games and cognitive developmental systems.
Applications of artificial intelligence in business, education and healthcare
Highlights the opportunities and challenges of artificial intelligence in business, education, and healthcare from institutional, environmental, social perspectives Includes empirical and theoretical research Presents applications of Artificial Intelligence in Business, Education and Healthcare
Applications and Theory of Petri Nets ; 29th International Conference, PETRI NETS 2008, Xi’an, China, June 23-27, 2008. Proceedings
This book constitutes the refereed proceedings of the 29th International Conference on Applications and Theory of Petri Nets and Other Models of Concurrency, PETRI NETS 2008, held in Xi'an, China, in June 2008.
Application of computational electromagnetics techniques and artificial intelligence in the engineering
Introduces the latest developments in electromagnetic computing and artificial intelligence technology. Artificial intelligence technology can be applied to the modeling, analysis, and optimization design of microwave equipment, solving the routing problem of self-organizing networks in small unmanned aerial vehicle systems, calculating the radiation characteristics of antenna arrays on large electrical platforms, analyzing the impact of electromagnetic wave coupling on electronic devices, simulating the field distribution characteristics of electronic devices, and so on. With the help of artificial intelligence, designers can more conveniently, quickly, and accurately solve engineering problems.
Anticipatory Behavior in Adaptive Learning Systems : From Brains to Individual and Social Behavior
Anticipatory behavior in adaptive learning systems is steadily gaining the - terest of scientists, although many researchers still do not explicitly consider the actual anticipatory capabilities of their systems.The introductory chapter of this volume therefore does not only provide an overview of the contributions included in this volume but also proposes a taxonomy of how anticipatory mechanisms can improve adaptive behavior and learning in cognitive systems. During the workshop it became clear that ant- ipations are involved in various cognitive processes that range from individual anticipatory mechanisms to social anticipatory behavior.
Ant Colony Optimization and Swarm Intelligence ; 6th International Conference, ANTS 2008, Brussels, Belgium, September 22-24, 2008. Proceedings
This book constitutes the refereed proceedings of the 6th International Workshop on Ant Colony Optimization and Swarm Intelligence, ANTS 2008, held in Brussels, Belgium, in September 2008.
Anisotropy Across Fields and Scales
This book focuses on processing, modeling, and visualization of anisotropy information…
Anatomy ontologies for bioinformatics : Principles and practice
This book provides a timely and first-of-its-kind collection of contributed chapters on anatomy ontologies. It is interdisciplinary in its approach, bringing together relevant expertise from computing and biomedical studies, and covering both theoretical and applied aspects, with an emphasis on newer work relevant to the emerging Semantic Web.
Analysis and Design of Information Systems : Third ed.
This third edition of the successful Analysis and Design of Information Systems provides a comprehensive introduction and user-friendly survey to all aspects of business transformation and analysis, and aims to provide the complex set of tools covering all types of systems, including legacy, transactional, database, and web/e-commerce topics.
An Introduction to Language Processing with Perl and Prolog : An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German
This book teaches the principles of natural language processing, first covering linguistics issues such as encoding, entropy, and annotation schemes; defining words, tokens and parts of speech; and morphology. It then details the language-processing functions involved, including part-of-speech tagging using rules and stochastic techniques; using Prolog to write phase-structure grammars; parsing techniques and syntactic formalisms; semantics, predicate logic and lexical semantics; and analysis of discourse, and applications in dialog systems. The key feature of the book is the author's hands-on approach throughout, with extensive exercises, sample code in Prolog and Perl, and a detailed introduction to Prolog. The reader is supported with a companion website that contains teaching slides, programs, and additional material.
An Introduction to Kolmogorov Complexity and Its Applications
Written by two experts in the field, this book is ideal for advanced undergraduate students, graduate students, and researchers in all fields of science. It is self-contained: it contains the basic requirements from mathematics, probability theory, statistics, information theory, and computer science. Included are history, theory, new developments, a wide range of applications, numerous (new) problem sets, comments, source references, and hints to solutions of problems. This is the only comprehensive treatment of the central ideas of Kolmogorov complexity and their applications.
