Image Processing Using Pulse-Coupled Neural Networks

This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly im

The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, object recognition, and clustering, with real-time implementations. It

Quickly obtain solutions to common Java image processing problems, learn best practices, and understand everything OpenCV has to offer for image processing. You will work with a JVM image wrapper to m

This book offers readers an essential introduction to the fundamentals of digital image processing. Pursuing a signal processing and algorithmic approach, it makes the fundamentals of digital image pr

This book introduces readers to innovative bio-inspired computing techniques for image processing applications. It demonstrates how a significant drawback of image processing – not providing the simul

Give your students a contemporary treatment of image processing that balances a broad coverage of major subject areas with in-depth examination of the most foundational topics. Birchfield's IMAGE PROC

This book provides comprehensive coverage of neural networks, their evolution, theirstructure, the problems they can solve, and their applications. The first halfof the book looks at theoretical inves

In this fundamental book the authors devise a framework that describes the working of the brain as a whole. It presents a comprehensive introduction to the principles of Neural Information Processing

If you are a competent C++ programmer and want to learn the tricks of image processing with OpenCV, then this book is for you. A basic understanding of image processing is required.

This book presents a broad overview on the current various design modules and applications of artificial neural systems. Artificial neural networks are often dubbed as one of the most acknowledged tec

The concepts as well as applications of various image processing techniques are elucidated in this comprehensive book. The book offers image processing principles and practical software implementation

For junior/graduate-level courses in Remote Sensing in Geography, Geology, Forestry, and Biology.Introductory Digital Image Processing: A Remote Sensing Perspectivefocuses on digital image processing

This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by introducing advanced models of neural networks. It overviews th

The Handbook of Document Image Processing and Recognition is a comprehensive resource on the latest methods and techniques in document image processing and recognition. Each chapter provides a clear o

The brand new edition of IMAGE PROCESSING, ANALYSIS, AND MACHINE VISION is a robust text providing deep and wide coverage of the full range of topics encountered in the field of image processing and m

This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities are discussed, including impulsive differential equations, d

"This book provides a comprehensive review of new developments in the study of language processing and related neural networks in schizophrenia by addressing the complex link between psychopathology,

Artificial neural networks are most suitable for solving problems that are complex, ill-defined, highly nonlinear, of many and different variables, and/or stochastic. Such problems are abundant in med

The primary purpose of this book is to show that a multilayer neural network can be considered as a multistage system, and then that the learning of this class of neural networks can be treated as a s

This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: Deep architectures Rec

The expression 'Neural Networks' refers traditionally to a class of mathematical algorithms that obtain their proper performance while they 'learn' from examples or from experience. As a consequence,

This book constitutes the refereed proceedings of the 13th International Conference on Engineering Applications of Neural Networks, EANN 2012, held in London, UK, in September 2012. The 49 revised ful

The aim of this book is to deal with biometrics in terms of signal and image processing methods and algorithms. This will help engineers and students working in digital signal and image processing dea

This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published in 2006, which lends itself to graduate and undergraduate cou

Continuing in the footsteps of the pioneering first edition, Signal and Image Processing for Remote Sensing, Second Edition explores the most up-to-date signal and image processing methods for dealing

This book comprises selected papers of the International Conference on Signal Processing, Image Processing and Pattern Recognition, SIP 2011, held as Part of the Future Generation Information Technolo

The three volume set LNCS 7062, LNCS 7063, and LNCS 7064 constitutes the proceedings of the 18th International Conference on Neural Information Processing, ICONIP 2011, held in Shanghai, China, in Nov

In recent years, Moore's law has fostered the steady growth of the field of digital image processing, though the computational complexity remains a problem for most of the digital image processing app

The two volume set LNCS 6443 and LNCS 6444 constitutes the proceedings of the 17th International Conference on Neural Information Processing, ICONIP 2010, held in Sydney, Australia, in November 2010.T

Originating from models of biological neural systems, artificial neural networks (ANN) are the cornerstones of artificial intelligence research. Catalyzed by the upsurge in computational power and ava

This book deals with new theoretical results for studying Cellular Neural Networks (CNNs) concerning its dynamical behavior. New aspects of CNNs' applications are developed for modelling of some famou

Lv et al. (Sichuan U., China) focus on the convergence analysis of subspace learning algorithms of neural networks and the ways to extend the use of these networks in fields like biomedical signal pro

The techniques and applications in the area of image processing and pattern recognition have been growing tremendously. Containing the latest state-of-the-art techniques for image processing and patt

Online learning from a signal processing perspective There is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced sign

A handbook on recent advancements and the state of the art in array processing and sensor Networks Handbook on Array Processing and Sensor Networks provides readers with a collection of tutorial arti

Illustrating essential aspects of adaptive image processing from a computational intelligence viewpoint, the second edition of Adaptive Image Processing: A Computational Intelligence Perspective provi

In this book, we aim to collect the most recent advances in artificial intelligence techniques (i.e. neural networks, fuzzy systems, multi-agent systems, genetic algorithms, image analysis, clustering

Image Processing with MATLABR: Applications in Medicine and Biology explains complex, theory-laden topics in image processing through examples and MATLABR algorithms. It describes classical as well em

Correlative Learning: A Basis for Brain and Adaptive Systems provides a bridge between three disciplines: computational neuroscience, neural networks, and signal processing. First, the authors lay dow

Artificial neural networks provide a powerful tool to help doctors analyse, model and make sense of complex clinical data across a broad range of medical applications. Their potential in clinical medicine is reflected in the diversity of topics covered in this volume. In addition to looking at applications the book looks forward to exciting future prospects. A section on theory looks at approaches to validate and refine the results generated by artificial neural networks. The volume also recognizes that concerns exist about the use of 'black-box' systems as decision aids in medicine, and the final chapter considers the ethical and legal conundrums arising out of their use for diagnostic or treatment decisions. Taken together, this eclectic collection of chapters provides an exciting overview of harnessing the power of artificial neural networks in the investigation and treatment of disease.