Object Detection and Recognition in Digital Images

Automatic speech recognition (ASR) is a very attractive means for human-machine interaction. The degree of maturity reached by speech recognition technologies during recent years allows the development of applications that use them. In particular, ASR shows an enormous potential in mobile environments, where devices such as mobile phones or PDAs are used, and for Internet Protocol (IP) applications. Speech Recognition Over Digital Channels is the first book of its kind to offer a complete system comprehension, addressing the topics of distributed and network-based speech recognition issues and standards, the concepts of speech processing and transmission, and system architectures and robustness. Describes the different client/server architectures for remote speech recognition systems, by means of which the client transmits speech parameters through a digital channel to a remote recognition server Focuses on robustness against both adverse acoustic environments (in the front-end) and bit errors/packet loss Discusses four ETSI standards for distributed speech recognition; the understanding of the standards and the technologies behind them Provides the necessary background for the comprehension of remote speech recognition technologies This book will appeal to a wide-ranging audience: engineers using speech recognition systems, researchers involved in ASR systems and those interested in processing and transmitting speech such as signal processing and communications communities. It will also be of interest to technical experts requiring an understanding of recognition over mobile and IP networks, and postgraduate students working on robust speech processing.

Moments as projections of an image’s intensity onto a proper polynomial basis can be applied to many different aspects of image processing. These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit invariants. In addition to the theory, attention is paid to efficient algorithms for moment computation in a discrete domain, and to computational aspects of orthogonal moments. The authors also illustrate the theory through practical examples, demonstrating moment invariants in real applications across computer vision, remote sensing and medical imaging. Key features: Presents a systematic review of the basic definitions and properties of moments covering geometric moments and complex moments. Considers invariants to traditional transforms – translation, rotation, scaling, and affine transform – from a new point of view, which offers new possibilities of designing optimal sets of invariants. Reviews and extends a recent field of invariants with respect to convolution/blurring. Introduces implicit moment invariants as a tool for recognizing elastically deformed objects. Compares various classes of orthogonal moments (Legendre, Zernike, Fourier-Mellin, Chebyshev, among others) and demonstrates their application to image reconstruction from moments. Offers comprehensive advice on the construction of various invariants illustrated with practical examples. Includes an accompanying website providing efficient numerical algorithms for moment computation and for constructing invariants of various kinds, with about 250 slides suitable for a graduate university course. Moments and Moment Invariants in Pattern Recognition is ideal for researchers and engineers involved in pattern recognition in medical imaging, remote sensing, robotics and computer vision. Post graduate students in image processing and pattern recognition will also find the book of interest.

Helps researchers in proteomics and oncology work together to understand, prevent, and cure cancer Proteomic data is increasingly important to understanding the origin and progression of cancer; however, most oncologic researchers who depend on proteomics for their studies do not collect the data themselves. As a result, there is a knowledge gap between scientists, who devise proteomic techniques and collect the data, and the oncologic researchers, who are expected to interpret and apply proteomic data. Bridging the gap between proteomics and oncology research, this book explains how proteomic technology can be used to address some of the most important questions in cancer research. Proteomic Applications in Cancer Detection and Discovery enables readers to understand how proteomic data is acquired and analyzed and how it is interpreted. Author Timothy Veenstra has filled the book with examples—many based on his own firsthand research experience—that clearly demonstrate the application of proteomic technology in oncology research, including the discovery of novel biomarkers for different types of cancers. The book begins with a brief introduction to systems biology, explaining why cancer is a systems biology disease. Next, it covers such topics as: Mass spectrometry in cancer research Application of proteomics to global phosphorylation analysis Search for biomarkers in biofluids Rise and fall of proteomic patterns for cancer diagnostics Emergence of protein arrays Role of proteomics in personalized medicine The final chapter is dedicated to the future prospects of proteomics in cancer research. By guiding readers through the latest proteomic technologies and their applications in cancer research, Proteomic Applications in Cancer Detection and Discovery enhances the ability of researchers in proteomics and researchers in oncology to collaborate in order to better understand cancer and develop strategies to prevent and treat it.

Prepared by world leaders on this topic, Biomarkers in Cancer Screening and Early Detection offers a comprehensive, state-of-the-art perspective on the various research and clinical aspects of cancer biomarkers, from their discovery and development to their validation, clinical utility, and use in developing personalized cancer treatment. Offers a comprehensive, state-of-the-art perspective on the various research and clinical aspects of cancer biomarkers Provides immediately actionable information ? and hopefully also inspiration ? to move discovery and clinical application forward Offers vital knowledge to help develop personalized cancer treatment for individual patients with specific cancers

A Timely Exploration of Multiuser Detection in Wireless Networks During the past decade, the design and development of current and emerging wireless systems have motivated many important advances in multiuser detection. This book fills an important need by providing a comprehensive overview of crucial recent developments that have occurred in this active research area. Each chapter is contributed by noted experts and is meant to serve as a self-contained treatment of the topic. Coverage includes: Linear and decision feedback methods Iterative multiuser detection and decoding Multiuser detection in the presence of channel impairments Performance analysis with random signatures and channels Joint detection methods for MIMO channels Interference avoidance methods at the transmitter Transmitter precoding methods for the MIMO downlink This book is an ideal entry point for exploring ongoing research in multiuser detection and for learning about the field's existing unsolved problems and issues. It is a valuable resource for researchers, engineers, and graduate students who are involved in the area of digital communications.

A Timely Exploration of Multiuser Detection in Wireless Networks During the past decade, the design and development of current and emerging wireless systems have motivated many important advances in multiuser detection. This book fills an important need by providing a comprehensive overview of crucial recent developments that have occurred in this active research area. Each chapter is contributed by noted experts and is meant to serve as a self-contained treatment of the topic. Coverage includes: Linear and decision feedback methods Iterative multiuser detection and decoding Multiuser detection in the presence of channel impairments Performance analysis with random signatures and channels Joint detection methods for MIMO channels Interference avoidance methods at the transmitter Transmitter precoding methods for the MIMO downlink This book is an ideal entry point for exploring ongoing research in multiuser detection and for learning about the field's existing unsolved problems and issues. It is a valuable resource for researchers, engineers, and graduate students who are involved in the area of digital communications.

State-of-the-art techniques for tapping the vast potential of polymers The use of specific non-covalent interactions to control polymer structure and properties is a rapidly emerging field with applications in diverse disciplines. Molecular Recognition and Polymers covers the fundamental aspects and applications of molecular recognition—in the creation of novel polymeric materials for use in drug delivery, sensors, tissue engineering, molecular imprinting, and other areas. This reference begins by explaining the fundamentals of supramolecular polymers; it progresses to cover polymer formation and self-assembly with a wide variety of examples, and then includes discussions of biomolecular recognition using polymers. With chapters contributed by the foremost experts in their fields, this resource: Provides an integrated resource for supramolecular chemistry, polymer science, and interfacial science Covers advanced, state-of-the-art techniques used in the design and characterization of non-covalent interactions in polymers Illustrates how to tailor the properties of polymeric materials for various applications Stand-alone chapters address specific applications independently for easy reference. This is a premier resource for graduate students and researchers in polymer chemistry, supramolecular chemistry, materials science, and physical organic chemistry.

Detect fraud faster—no matter how well hidden—with IDEA automation Fraud and Fraud Detection takes an advanced approach to fraud management, providing step-by-step guidance on automating detection and forensics using CaseWare's IDEA software. The book begins by reviewing the major types of fraud, then details the specific computerized tests that can detect them. Readers will learn to use complex data analysis techniques, including automation scripts, allowing easier and more sensitive detection of anomalies that require further review. The companion website provides access to a demo version of IDEA, along with sample scripts that allow readers to immediately test the procedures from the book. Business systems' electronic databases have grown tremendously with the rise of big data, and will continue to increase at significant rates. Fraudulent transactions are easily hidden in these enormous datasets, but Fraud and Fraud Detection helps readers gain the data analytics skills that can bring these anomalies to light. Step-by-step instruction and practical advice provide the specific abilities that will enhance the audit and investigation process. Readers will learn to: Understand the different areas of fraud and their specific detection methods Identify anomalies and risk areas using computerized techniques Develop a step-by-step plan for detecting fraud through data analytics Utilize IDEA software to automate detection and identification procedures The delineation of detection techniques for each type of fraud makes this book a must-have for students and new fraud prevention professionals, and the step-by-step guidance to automation and complex analytics will prove useful for even experienced examiners. With datasets growing exponentially, increasing both the speed and sensitivity of detection helps fraud professionals stay ahead of the game. Fraud and Fraud Detection is a guide to more efficient, more effective fraud identification.

Today’s networks of processors on and off chip, operating with independent clocks, need effective synchronization of the data passing between them for reliability. When two or more processors request access to a common resource, such as a memory, an arbiter has to decide which request to deal with first. Current developments in integrated circuit processing are leading to an increase in the numbers of independent digital processing elements in a single system. With this comes faster communications, more networks on chip, and the demand for more reliable, more complex, and higher performance synchronizers and arbiters. Written by one of the foremost researchers in this area of digital design, this authoritative text provides in-depth theory and practical design solutions for the reliable working of synchronization and arbitration hardware in digital systems. The book provides methods for making real reliability measurements both on and off chip, evaluating some of the common difficulties and detailing circuit solutions at both circuit and system levels. Synchronization and Arbitration in Digital Systems also presents: mathematical models used to estimate mean time between failures in digital systems; a summary of serial and parallel communication techniques for on-chip data transmission; explanations on how to design a wrapper for a locally synchronous cell, highlighting the issues associated with stoppable clocks; an examination of various types of priority arbiters, using signal transition graphs to show the specification of different designs (from the simplest to more complex multi-way arbiters) including ways of solving problems encountered in a wide range of applications; essential information on systems composed of independently timed regions, including a discussion on the problem of choice and the factors affecting the time taken to make choices in electronics. With its logical approach to design methodology, this will prove an invaluable guide for electronic and computer engineers and researchers working on the design of digital electronic hardware. Postgraduates and senior undergraduate students studying digital systems design as part of their electronic engineering course will struggle to find a resource that better details the information given inside this book

A comprehensive overview of high-performance pattern recognition techniques and approaches to Computational Molecular Biology This book surveys the developments of techniques and approaches on pattern recognition related to Computational Molecular Biology. Providing a broad coverage of the field, the authors cover fundamental and technical information on these techniques and approaches, as well as discussing their related problems. The text consists of twenty nine chapters, organized into seven parts: Pattern Recognition in Sequences, Pattern Recognition in Secondary Structures, Pattern Recognition in Tertiary Structures, Pattern Recognition in Quaternary Structures, Pattern Recognition in Microarrays, Pattern Recognition in Phylogenetic Trees, and Pattern Recognition in Biological Networks. Surveys the development of techniques and approaches on pattern recognition in biomolecular data Discusses pattern recognition in primary, secondary, tertiary and quaternary structures, as well as microarrays, phylogenetic trees and biological networks Includes case studies and examples to further illustrate the concepts discussed in the book Pattern Recognition in Computational Molecular Biology: Techniques and Approaches is a reference for practitioners and professional researches in Computer Science, Life Science, and Mathematics. This book also serves as a supplementary reading for graduate students and young researches interested in Computational Molecular Biology.