The use of neural networks is permeating every area of signal processing. They can provide powerful means for solving many problems, especially in nonlinear, real-time, adaptive, and blind signal processing. The Handbook of Neural Network Signal Processing brings together applications that were previously scattered among various publications to provide an up-to-date, detailed treatment of the subject from an engineering point of view.

The authors cover basic principles, modeling, algorithms, architectures, implementation procedures, and well-designed simulation examples of audio, video, speech, communication, geophysical, sonar, radar, medical, and many other signals. The subject of neural networks and their application to signal processing is constantly improving. You need a handy reference that will inform you of current applications in this new area. The Handbook of Neural Network Signal Processing provides this much needed service for all engineers and scientists in the field.

As multimedia applications have become part of contemporary daily life, numerous paradigm-shifting technologies in multimedia processing have emerged over the last decade. Substantially updated with 21 new chapters, Multimedia Image and Video Processing, Second Edition explores the most recent advances in multimedia research and applications. This edition presents a comprehensive treatment of multimedia information mining, security, systems, coding, search, hardware, and communications as well as multimodal information fusion and interaction. Clearly divided into seven parts, the book begins with a section on standards, fundamental methods, design issues, and typical architectures. It then focuses on the coding of video and multimedia content before covering multimedia search, retrieval, and management. After examining multimedia security, the book describes multimedia communications and networking and explains the architecture design and implementation for multimedia image and video processing. It concludes with a section on multimedia systems and applications. Written by some of the most prominent experts in the field, this updated edition provides readers with the latest research in multimedia processing and equips them with advanced techniques for the design of multimedia systems.

Illustrating essential aspects of adaptive image processing from a computational intelligence viewpoint, the second edition of Adaptive Image Processing: A Computational Intelligence Perspective provides an authoritative and detailed account of computational intelligence (CI) methods and algorithms for adaptive image processing in regularization, edge detection, and early vision.

With three new chapters and updated information throughout, the new edition of this popular reference includes substantial new material that focuses on applications of advanced CI techniques in image processing applications. It introduces new concepts and frameworks that demonstrate how neural networks, support vector machines, fuzzy logic, and evolutionary algorithms can be used to address new challenges in image processing, including low-level image processing, visual content analysis, feature extraction, and pattern recognition.

Emphasizing developments in state-of-the-art CI techniques, such as content-based image retrieval, this book continues to provide educators, students, researchers, engineers, and technical managers in visual information processing with the up-to-date understanding required to address contemporary challenges in image content processing and analysis.

A complete lexicon of technical information, the Dictionary of Computer Science, Engineering, and Technology provides workable definitions, practical information, and enhances general computer science and engineering literacy. It spans various disciplines and industry sectors such as: telecommunications, information theory, and software and hardware systems. If you work with, or write about computers, this dictionary is the single most important resource you can put on your shelf.
The dictionary addresses all aspects of computing and computer technology from multiple perspectives, including the academic, applied, and professional vantage points. Including more than 8,000 terms, it covers all major topics from artificial intelligence to programming languages, from software engineering to operating systems, and from database management to privacy issues. The definitions provided are detailed rather than concise.
Written by an international team of over 80 contributors, this is the most comprehensive and easy-to-read reference of its kind. If you need to know the definition of anything related to computers you will find it in the Dictionary of Computer Science, Engineering, and Technology.

As multimedia applications have become part of contemporary daily life, numerous paradigm-shifting technologies in multimedia processing have emerged over the last decade. Substantially updated with 21 new chapters, Multimedia Image and Video Processing, Second Edition explores the most recent advances in multimedia research and applications. This edition presents a comprehensive treatment of multimedia information mining, security, systems, coding, search, hardware, and communications as well as multimodal information fusion and interaction. Clearly divided into seven parts, the book begins with a section on standards, fundamental methods, design issues, and typical architectures. It then focuses on the coding of video and multimedia content before covering multimedia search, retrieval, and management. After examining multimedia security, the book describes multimedia communications and networking and explains the architecture design and implementation for multimedia image and video processing. It concludes with a section on multimedia systems and applications. Written by some of the most prominent experts in the field, this updated edition provides readers with the latest research in multimedia processing and equips them with advanced techniques for the design of multimedia systems.

While most books on the subject focus on resource allocation in just one type of network, this book is the first to examine the common characteristics of multiple distributed video communication systems. Comprehensive and systematic, Optimal Resource Allocation for Distributed Video Communication presents a unified optimization framework for resource allocation across these systems. The book examines the techniques required for optimal resource allocation over Internet, wireless cellular networks, wireless ad hoc networks, and wireless sensor networks. It provides you with the required foundation in video communications, including Peer-to-Peer (P2P) networks, wireless networks, and visual sensor networks. Whether you're in industry or academia, you'll value how the book outlines current challenges facing the field and outlines a general solution framework for addressing these challenges. From problem formulations and theoretical analysis to practical algorithms, it facilitates the comprehensive understanding required to achieve optimized video and multimedia communications. Presents the resource allocation techniques for scalable video communications over Internet or wireless networks Examines two resource allocation problems-distributed throughput maximization for scalable P2P Video-on-Demand (VoD) systems and streaming capacity for P2P VoD systems Outlines an optimal prefetching framework for reducing seeking delays in P2P VoD applications Examines distributed optimization techniques for unicast and multicast video streaming over wireless ad hoc networks Considers the network lifetime maximization problem in wireless visual sensor networks Detailing methods that can immediately improve the performance of your video communication systems, this book presents multiple applications of optimal resource allocation. For each of the applications,

In recent years there has been a growing interest in improving all aspects of the interaction between human and computers. Emotion recognition is a new technique based on affective computing that is expected to significantly improve the quality of human-computer interaction system and communications. Most existing works address this problem using 2D features, but they are sensitive to head pose, clutter, and variations in lighting conditions. In light of such problems, two 3D visual feature based approaches are presented, the 3D Gabor feature and the 3D elastic body spline features from video sequences. The most significant contributions of this work are detecting and tracking fiducial points automatically from video sequences to construct a generic 3D face model, and the introduction of EBS deformation features for emotion recognition. These methods open a new research direction for human computer communication with applications to security systems, the intelligent home, a learning environment, and educational software.

-Presents state-of-the-art in visual media retrieval.

-Coverage of adaptive content-based retrieval systems and techniques in image and video database applications.

-Includes a novel machine-controlled interactive retrieval (MCIR) method that optimizes image search in distributed digital libraries over the Internet.

This book deals with adaptive content-based retrieval systems and techniques in image and video database applications. It discusses key considerations in the development of these methods, and demonstrates their performance. It first introduces a perceptually inspired non-linear paradigm in user-controlled interactive retrieval (UCIR), providing an effective tool to bridge the perceptual gap between high-level semantics in human vision and low-level features used by computers. Then, a novel machine-controlled interactive retrieval (MCIR) method is presented to optimize image search in distributed digital libraries over Internet, by minimizing bandwidth requirement in retrieval and reducing human subjective errors. The adaptive methodologies and techniques are then generalized to content analysis and retrieval of video data with time-varying nature, which provide multiple-level access to a large quantity of digital videos. Finally, the UCIR and MCIR systems are demonstrated by applications ranging from Digital Asset Management (DAM), Geographical Database Retrieval, Searching and Retrieval of Art Documents, and Film and Video Retrieval.

While most books on the subject focus on resource allocation in just one type of network, this book is the first to examine the common characteristics of multiple distributed video communication systems. Comprehensive and systematic, Optimal Resource Allocation for Distributed Video Communication presents a unified optimization framework for resource allocation across these systems. The book examines the techniques required for optimal resource allocation over Internet, wireless cellular networks, wireless ad hoc networks, and wireless sensor networks. It provides you with the required foundation in video communications, including Peer-to-Peer (P2P) networks, wireless networks, and visual sensor networks. Whether you're in industry or academia, you'll value how the book outlines current challenges facing the field and outlines a general solution framework for addressing these challenges. From problem formulations and theoretical analysis to practical algorithms, it facilitates the comprehensive understanding required to achieve optimized video and multimedia communications. Presents the resource allocation techniques for scalable video communications over Internet or wireless networks Examines two resource allocation problems-distributed throughput maximization for scalable P2P Video-on-Demand (VoD) systems and streaming capacity for P2P VoD systems Outlines an optimal prefetching framework for reducing seeking delays in P2P VoD applications Examines distributed optimization techniques for unicast and multicast video streaming over wireless ad hoc networks Considers the network lifetime maximization problem in wireless visual sensor networks Detailing methods that can immediately improve the performance of your video communication systems, this book presents multiple applications of optimal resource allocation. For each of the applications,