This book constitutes the refereed proceedings of the 24th Conference on Artificial Intelligence, Canadian AI 2011, held in St. John's, Canada, in May 2011. The 23 revised full papers presented together with 22 revised short papers and 5 papers from the graduate student symposium were carefully reviewed and selected from 81 submissions. The papers cover a broad range of topics presenting original work in all areas of artificial intelligence, either theoretical or applied.

This book constitutes the proceedings of the Second International Conference on Information Processing in Computer-Assisted Interventions IPCAI 2011, held in Berlin, Germany, on June 22, 2011. The 17 papers presented were carefully reviewed and selected from 29 submissions. The focus of the conference is the use of information technology in interventional medicine, including real-time modeling and analysis, technology, human-machine interfaces, and systems associated with operating rooms and interventional suites. It also covers the overall information flow associated with intervention planning, execution, follow-up, and outcome analysis; as well as training and skill assessment for such procedures.

This book constitutes the refereed proceedings of the Second International Conference on Autonomous and Intelligent Systems, AIS 2011, held in Burnaby, BC, Canada, in June 2011, colocated with the International Conference on Image Analysis and Recognition, IACIAR 2011.
The 40 revised full papers presented were carefully reviewed and selected from 62 submissions. The papers are organized in topical sections on autonomous and intelligent systems, intelligent and advanced control systems, intelligent sensing and data analysis, human-machine interaction, and intelligent circuit analysis and signal processing.

This two-volume set (CCIS 150 and CCIS 151) constitutes the refereed proceedings of the Second International Conference on Ubiquitous Computing and Multimedia Applications, UCMA 2011, held in Daejeon, Korea, in April 2011. The 86 revised full papers presented were carefully reviewed and selected from 570 submissions. Focusing on various aspects of advances in multimedia applications and ubiquitous computing with computational sciences, mathematics and information technology the papers present current research in the area of multimedia and ubiquitous environment including models and systems, new directions, novel applications associated with the utilization, and acceptance of ubiquitous computing devices and systems.

This book constitutes the refereed proceedings of the 9th International Conference on Smart Homes and Health Telematics, ICOST 2011, held in Montreal, Canada, in June 2011. The 25 revised full papers presented together with 16 short papers and 8 student papers were carefully reviewed and selected from 94 submissions. The papers are organized in topical sections on smart home and village; health telematics and healthcare technology; wellbeing, ageing friendly and enabling technology; and medical health telematics and healthcare technology.

This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2011, held in Torino, Italy, in April 2011. The 22 revised full papers presented were carefully reviewed and selected from 42 submissions. The papers present the latest research and discuss current developments and applications in metaheuristics - a paradigm to effectively solve difficult combinatorial optimization problems appearing in various industrial, economical, and scientific domains. Prominent examples of metaheuristics are evolutionary algorithms, simulated annealing, tabu search, scatter search, memetic algorithms, variable neighborhood search, iterated local search, greedy randomized adaptive search procedures, estimation of distribution algorithms, and ant colony optimization.

This volume constitutes the refereed proceedings of the 14th International Workshop on Combinatorial Image Analysis, IWCIA 2011, held in Madrid, Spain, in May 2011. The 25 revised full papers and 13 poster papers presented together with 4 invited contributions were carefully reviewed and selected from 60 submissions. The papers are organized in topical sections such as combinatorial problems in the discrete plane and space related to image analysis; lattice polygons and polytopes; discrete/combinatorial geometry and topology and their use in image analysis; digital geometry of curves and surfaces; tilings and patterns; combinatorial pattern matching; image representation, segmentation, grouping, and reconstruction; methods for image compression; discrete tomography; applications of integer programming, linear programming, and computational geometry to problems of image analysis; parallel architectures and algorithms for image analysis; fuzzy and stochastic image analysis; grammars and models for image or scene analysis and recognition, cellular automata; mathematical morphology and its applications to image analysis; applications in medical imaging, biometrics, and others.

The Radial Basis Function (RBF) network has gained in popularity in recent years. This is due to its desirable properties in classification and functional approximation applications, accompanied by training that is more rapid than that of many other neural-network techniques. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of applications areas, for example, robotics, biomedical engineering, and the financial sector. The two-title series Theory and Applications of Radial Basis Function Networks provides a comprehensive survey of recent RBF network research. This volume, New Advances in Design, contains a wide range of applications in the laboratory and case-studies describing current use. The sister volume to this one, Recent Developments in Theory and Applications, covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms. The combination of the two volumes will prove extremely useful to practitioners in the field, engineers, researchers, students and technically accomplished managers.

The three-volume set LNCS 6675, 6676 and 6677 constitutes the refereed proceedings of the 8th International Symposium on Neural Networks, ISNN 2011, held in Guilin, China, in May/June 2011. The total of 215 papers presented in all three volumes were carefully reviewed and selected from 651 submissions. The contributions are structured in topical sections on computational neuroscience and cognitive science; neurodynamics and complex systems; stability and convergence analysis; neural network models; supervised learning and unsupervised learning; kernel methods and support vector machines; mixture models and clustering; visual perception and pattern recognition; motion, tracking and object recognition; natural scene analysis and speech recognition; neuromorphic hardware, fuzzy neural networks and robotics; multi-agent systems and adaptive dynamic programming; reinforcement learning and decision making; action and motor control; adaptive and hybrid intelligent systems; neuroinformatics and bioinformatics; information retrieval; data mining and knowledge discovery; and natural language processing.

Ziel des Workshops "Bildverarbeitung fur die Medizin" ist die Prasentation aktueller Forschungsergebnisse und die Vertiefung des Gesprachs zwischen Wissenschaftlern, Industrie und Anwendern. Die Beitrage dieses Bandes behandeln alle Bereiche der medizinischen Bildverarbeitung, darunter insbesondere die Themen molekulare Bildgebung, Animation, patientenindividuelle Simulation und Planung, computerunterstutzte Diagnose, biomechanische Modellierung, Bildverarbeitung in der Telemedizin, bildgestutzte Roboter und chirurgische Simulatoren.

The NATO Advanced Research Workshop on Signal Processing and Pattern Recognition in Nondestructive Evaluation (NOE) of Materials was held August 19-22, 1987 at the Manoir St-Castin, Lac Beauport, Quebec, Canada. Modern signal processing, pattern recognition and artificial intelligence have been playing an increasingly important role in improving nondestructive evaluation and testing techniques. The cross fertilization of the two major areas can lead to major advances in NOE as well as presenting a new research area in signal processing. With this in mind, the Workshop provided a good review of progress and comparison of potential techniques, as well as constructive discussions and suggestions for effective use of modern signal processing to improve flaw detection, classification and prediction, as well as material characterization. This Proceedings volume includes most presentations given at the Workshop. This publication, like the meeting itself, is unique in the sense that it provides extensive interactions among the interrelated areas of NOE. The book starts with research advances on inverse problems and then covers different aspects of digital waveform processing in NOE and eddy current signal analysis. These are followed by four papers of pattern recognition and AI in NOE, and five papers of image processing and reconstruction in NOE. The last two papers deal with parameter estimation problems. Though the list of papers is not extensive, as the field of NOE signal processing is very new, the book has an excellent collection of both tutorial and research papers in this exciting new field.

Surface properties play a very important role in many perception tasks. Object recognition, navigation, and inspection use surface properties ex tensively. Characterizing surfaces at different scales in given data is often the first and possibly the most important step. Most early research in ma chine perception relied on only very coarse characterization of surfaces. In the last few years, surface characterization has been receiving due attention. Dr. T. J. Fan is one of the very few researchers who designed and im plemented a complete system for object recognition. He studied issues re lated to characterization of surfaces in the context of object recognition, and then uses the features thus developed for recognizing objects. He uses a multi-view representation of 3-D objects for recognition, and he devel ops techniques for the segmentation of range images to obtain features for recognition. His matching approach also allows him to recognize objects from their partial views in the presence of other occluding objects. The efficacy of his approach is demonstrated in many examples."

This book constitutes the refereed proceedings of the 16th IAPR International Conference on Discrete Geometry for Computer Imagery, DGCI 2011, held in Nancy, France, in April 2011.
The 20 revised full papers and 20 revised poster papers presented together with 3 invited lectures were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on models for discrete geometry, discrete and combinatorial topology, geometric transforms, discrete shape representation, recognition and analysis, discrete tomography, morphological analysis, as well as discrete and combinatorial tools for image segmentation and analysis.

As is true with most areas of Artificial Intelligence, there is real need for a symbiotic relationship between the biological and artificial - a need for problems to be viewed from many different angles, and particularly so in the study of vision. The INSIGHT consortium is taking steps in this direction. In a traditional sense, the papers in this volume are represented by the areas of neuroscience, psychophysics and traditional computer vision. However, to gain deeper insight into vision processes, it is the interaction of scientific ideas from these areas that is essential. The scope of the topics discussed has a definite interdisciplinary flavour: at one end of the spectrum we have experiments performed and direct measurement of the responses of neurons to visual stimuli; at the other end we have the mathematical and computational aspects of optical flow (the relative motion between observer and object) and approaches of tackling vision through binocular disparities (stereopsis). Traditional edge detection (essential for the initial classification of shape) is also covered as is the study of natural texture patterns that occur on object surfaces. A fundamental aim of the Basic Research part of the ESPRIT programme is the pro duction and maintenance of a pool of research expertise in Europe, from which both fur ther research and industry can draw. As the authors state in their preface, this project has not only succesfully merged the talents of senior researchers from different backgrounds, but also brought many young ones along."

The topic of level sets is currently very timely and useful for creating realistic 3-D images and animations. They are powerful numerical techniques for analyzing and computing interface motion in a host of application settings. In computer vision, it has been applied to stereo and segmentation, whereas in graphics it has been applied to the postproduction process of in-painting and 3-D model construction. Osher is co-inventor of the Level Set Methods, a pioneering framework introduced jointly with James Sethian from the University of Berkeley in 1998. This methodology has been used up to now to provide solutions to a wide application range not limited to image processing, computer vision, robotics, fluid mechanics, crystallography, lithography, and computer graphics. The topic is of great interest to advanced students, professors, and R&D professionals working in the areas of graphics (post-production), video-based surveillance, visual inspection, augmented reality, document image processing, and medical image processing. These techniques are already employed to provide solutions and products in the industry (Cognitech, Siemens, Philips, Focus Imaging). An essential compilation of survey chapters from the leading researchers in the field, emphasizing the applications of the methods. This book can be suitable for a short professional course related with the processing of visual information.

Unique blend of asymptotic theory and small sample practice through simulation experiments and data analysis.

Novel reproducing kernel Hilbert space methods for the analysis of smoothing splines and local polynomials. Leading to uniform error bounds and honest confidence bands for the mean function using smoothing splines

Exhaustive exposition of algorithms, including the Kalman filter, for the computation of smoothing splines of arbitrary order.

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 November 2011.
The 262 regular session papers presented were carefully reviewed and selected from numerous submissions. The papers of part I are organized in topical sections on perception, emotion and development, bioinformatics, biologically inspired vision and recognition, bio-medical data analysis, brain signal processing, brain-computer interfaces, brain-like systems, brain-realistic models for learning, memory and embodied cognition, Clifford algebraic neural networks, combining multiple learners, computational advances in bioinformatics, and computational-intelligent human computer interaction. The second volume is structured in topical sections on cybersecurity and data mining workshop, data mining and knowledge doscovery, evolutionary design and optimisation, graphical models, human-originated data analysis and implementation, information retrieval, integrating multiple nature-inspired approaches, kernel methods and support vector machines, and learning and memory. The third volume contains all the contributions connected with multi-agent systems, natural language processing and intelligent Web information processing, neural encoding and decoding, neural network models, neuromorphic hardware and implementations, object recognition, visual perception modelling, and advances in computational intelligence methods based pattern recognition.

The two-volume set LNCS 7066 and LNCS 7067 constitutes the proceedings of the Second International Visual Informatics Conference, IVIC 2011, held in Selangor, Malaysia, during November 9-11, 2011. The 71 revised papers presented were carefully reviewed and selected for inclusion in these proceedings. They are organized in topical sections named computer vision and simulation; virtual image processing and engineering; visual computing; and visualisation and social computing. In addition the first volume contains two keynote speeches in full paper length, and one keynote abstract.

The 30 coherently written chapters by leading researchers presented in this anthology are devoted to basic results achieved in computational intelligence since 1997. The book provides complete coverage of the core issues in the field, especially in fuzzy logic and control as well as for evolutionary optimization algorithms including genetic programming, in a comprehensive and systematic way. Theoretical and methodological investigations are complemented by prototypic applications for design and management tasks in electrical engineering, mechanical engineering, and chemical engineering.
This book will become a valuable source of reference for researchers active in computational intelligence. Advanced students and professionals interested in learning about and applying advanced techniques of computational intelligence will appreciate the book as a useful guide enhanced by numerous examples and applications in a variety of fields.

In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as artificial intelligence and statistics. This carefully edited monograph is a compendium of the most recent advances in the area of probabilistic graphical models such as decision graphs, learning from data and inference. It presents a survey of the state of the art of specific topics of recent interest of Bayesian Networks, including approximate propagation, abductive inferences, decision graphs, and applications of influence. In addition, Advances in Bayesian Networks presents a careful selection of applications of probabilistic graphical models to various fields such as speech recognition, meteorology or information retrieval.

The book presents new clustering schemes, dynamical systems and pattern recognition algorithms in geophysical, geodynamical and natural hazard applications. The original mathematical technique is based on both classical and fuzzy sets models. Geophysical and natural hazard applications are mostly original. However, the artificial intelligence technique described in the book can be applied far beyond the limits of Earth science applications. The book is intended for research scientists, tutors, graduate students, scientists in geophysics and engineers

This book thoroughly surveys and examines advances in fingerprint sensing devices and in algorithms for fingerprint image analysis and matching. After an opening chapter on the history of fingerprint recognition, "Automatic Fingerprint Recognition Systems" moves into new technologies for inkless sensors, fingerprint image analysis techniques, including fingerprint video analysis, filtering and classification and other areas aimed at fully automatic operation. The book also addresses large-scale fingerprint identification system design, as well as standards.

Topics and Features:

* Covers numerous areas related to modern automatic fingerprint recognition, not just its history or forensic analysis

* Examines advances in fingerprint sensing and fingerprint image filtering and preprocessing

* Describes fingerprint feature abstraction, as well as compression and decompression of fingerprint images

* Develops ideas related to large-scale, large-database fingerprint matching

* Assesses such important areas as security in fingerprint matching and the common criterion protection profile

This authoritative survey provides a unique reference for automatic fingerprint recognition concepts, technologies, and systems. Its editors and contributors are leading researchers and applied R&D developers of this technology. Biometrics and pattern recognition researchers, security professionals, and systems developers will find the work an indispensable resource for current knowledge and technology.

This book presents a novel approach to neural nets and thus offers a genuine alternative to the hitherto known neuro-computers. The new edition includes a section on transformation properties of the equations of the synergetic computer and on the invariance properties of the order parameter equations. Further additions are a new section on stereopsis and recent developments in the use of pulse-coupled neural nets for pattern recognition.

Science has made great progress in the twentieth century, with the establishment of proper disciplines in the fields of physics, computer science, molecular biology, and many others. At the same time, there have also emerged many engineering ideas that are interdisciplinary in nature, beyond the realm of such orthodox disciplines. These in clude, for example, artificial intelligence, fuzzy logic, artificial neural networks, evolutional computation, data mining, and so on. In or der to generate new technology that is truly human-friendly in the twenty-first century, integration of various methods beyond specific disciplines is required. Soft computing is a key concept for the creation of such human friendly technology in our modern information society. Professor Rutkowski is a pioneer in this field, having devoted himself for many years to publishing a large variety of original work. The present vol ume, based mostly on his own work, is a milestone in the devel opment of soft computing, integrating various disciplines from the fields of information science and engineering. The book consists of three parts, the first of which is devoted to probabilistic neural net works. Neural excitation is stochastic, so it is natural to investi gate the Bayesian properties of connectionist structures developed by Professor Rutkowski. This new approach has proven to be par ticularly useful for handling regression and classification problems vi Preface in time-varying environments. Throughout this book, major themes are selected from theoretical subjects that are tightly connected with challenging applications."

The related fields of fractal image encoding and fractal image analysis have blossomed in recent years. This book, originating from a NATO Advanced Study Institute held in 1995, presents work by leading researchers. It is developing the subjects at an introductory level, but it also has some recent and exciting results in both fields.
The book contains a thorough discussion of fractal image compression and decompression, including both continuous and discrete formulations, vector space and hierarchical methods, and algorithmic optimizations. The book also discusses multifractal approaches to image analysis, segmentation, and recognition, including medical applications.