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Books > Computing & IT > Applications of computing > Pattern recognition
This volume presents the proceedings of the 6th International
Symposium on Combinatorial Pattern Matching, CPM '95, held in
Espoo, Finland in July 1995.
The papers that appear in this volume are refereed versions of presenta tions made at the third Neural Computation and Psychology Workshop, held at Stirling University, Scotland, from 31 August to 2 September 1994. The aim of this series of conferences has been to explore the interface between Neural Computing and Psychology: this has been a fruitful area for many researchers for a number of reasons. The development ofNeural Computation has supplied tools to researchers in Cognitive Neuroscience, allowing them to look at possible mechanisms for implementing theories which would otherwise remain 'black box' techniques. These theories may be high-level theories, concerned with interaction between a number of brain areas, or low-level, describing the way in which smaller local groups of neurons behave. Neural Computation techniques have allowed computer scientists to implement systems which are based on how real brains appear to function, providing effective pattern recognition systems. We can thus mount a two-pronged attack on perception. The papers here come from both the Cognitive Psychology viewpoint and from the Computer Science viewpoint: it is a mark of the growing maturity of the interface between the two subjects that they can under stand each other's papers, and the level of discussion at the workshop itself showed how important each camp considers the other to be. The papers here are divided into four sections, reflecting the primary areas of the material."
This volume presents the proceedings of the Fifth Annual Symposium on Combinatorial Pattern Matching, held at Asilomar, California, in June 1994. The 26 selected papers in this volume are organized in chapters on Alignments, Various Matchings, Combinatorial Aspects, and Bio-Informatics. Combinatorial Pattern Matching addresses issues of searching and matching of strings and more complicated patterns, as for example trees. The goal is to derive non-trivial combinatorial properties for such structures and then to exploit these properties in order to achieve superior performance for the corresponding computational problems. In recent years, combinatorial pattern matching has developed into a full-fledged area of algorithmics and is expected to grow even further during the next years.
This book contains the written contributions to the program of the First In ternational Conference on Computer Vision, Virtual Reality, and Robotics in Medicine (CVRMed'95) held in Nice during the period April 3-6, 1995. The articles are regrouped into a number of thematic sessions which cover the three major topics of the field: medical image understanding, registration problems in medicine, and therapy planning, simulation and control. The objective of the conference is not only to present the most innovative and promising research work but also to highlight research trends and to foster dialogues and debates among participants. This event was decided after a preliminary successful symposium organized in Stanford in March 1994 by E. Grimson (MIT), T. Kanade (CMU), R. Kikinis and W. Wells (Chair) (both at Harvard Medical School and Brigham and Women's Hospital), and myself (INRIA). We received 92 submitted full papers, and each one was evaluated by at least three members of the Program Committee, with the help of auxiliary reviewers. Based on these evaluations, a representative subset of the Program Committee met to select 19 long papers, 29 regular papers, and 27 posters. The geographical repartition of the contributions is the following: 24 from European countries (other than France), 23 contributions from France, 20 from Northern America (USA and Canada), and 8 from Asia (Japan and Singapore).
The research area of graph grammars and graph transformations dates back only two decades. But already methods and results from the area of graph transformation have been applied in many fields of computer science, such as formal language theory, pattern recognition and generation, compiler construction, software engineering, concurrent and distributed systems modelling, and database design and theory. This volume contains 24 selected and revised papers from an international seminar held in Dagstuhl, Germany, in 1993. The papers cover topics in the following areas: foundations of graph grammars and transformations; and applications of graph transformations to concurrent computing, specification and programming, and pattern generation and recognition.
This monograph presents the author's studies in music recognition aimed at developing a computer system for automatic notation of performed music. The performance of such a system is supposed to be similar to that of speech recognition systems: acoustical data at the input and music scoreprinting at the output. The approach to pattern recognition employed is thatof artificial perception, based on self-organizing input data in order to segregate patterns before their identification by artificial intelligencemethods. The special merit of the approach is that it finds optimal representations of data instead of directly recognizing patterns.
This volume constitutes the proceedings of the 5th International Conference on Computer Analysis of Images and Patterns (CAIP'93), held in Budapest, Hungary, in September 1993. Formerly, the events in this biennial conference series were thought as a forum where East European researchers and professionals from academia and industry had an opportunity to discuss their results and ideas with Western colleagues active in image processing and pattern recognition. Now, CAIP'93 has a much more international scope, and in the future these conferences will not any longertake place only in East European countries, but roam throughout whole Europe. Besides invited talks by Belikova, Gimel'farb, Haralick and Roska, the volume contains 114 contributions, either presented as lectures or posters and carefully selected by a highly competent international program committee from a total of some 230 submissions; thus the book gives a thorough survey on recent research results and their applications in image processing and pattern recognition. The proceedings is organized in 20 sections, for example on image data structures, image processing, edges and contours, Hough transforms and related methods, shape, motion, 3-D vision, character recognition and document processing, biomedical applications, industrial applications, and neural networks.
Given a familiar object extracted from its surroundings, we humans have little difficulty in recognizing it irrespective of its size, position and orientation in our field of view. Changes in lighting and the effects of perspective also pose no problems. How do we achieve this, and more importantly, how can we get a computer to do this? One very promising approach is to find mathematical functions of an object's image, or of an object's 3D description, that are invariant to the transformations caused by the object's motion. This book is devoted to the theory and practice of such invariant image features, so-called image invariants, for planar objects. It gives a comprehensive summary of the field, discussing methods for recognizing both occluded and partially occluded objects, and also contains a definitive treatmentof moment invariants and a tutorial introduction to algebraic invariants, which are fundamental to affine moment invariants and to many projective invariants. A number of novel invariant functions are presented and the results of numerous experiments investigating the stability of new and old invariants are discussed. The main conclusion is that moment invariants are very effective, both for partially occluded objects and for recognizing objects in grey-level images.
Die optische Ortsfiltertechnik wird vorrangig zur einkomponentigen (1C) Geschwindigkeits- und Langenbestimmung bei der beruhrungslosen Uberwachung industrieller Prozesse angewendet. Martin Schaeper beschaftigt sich mit der fortfuhrenden Nutzung von flachenhaften, strukturierten Sensoren fur zeitaufgeloste 2D/2C-Messungen, aber auch mit der Implementierung geeigneter Informationsvorverarbeitungen, um eine hohere Abtastung des vorliegenden Prozesses zu erreichen. Ausgehend von der Entstehung des Ortsfiltersignals wird dieses weiterfuhrend als zeitabhangiger Fourier-Koeffizient aufgefasst. Anhand von Hochgeschwindigkeitsbildfolgen stellt der Autor die ortsfilterbasierte Offline-2D/2C-Messung dar. Darauf aufbauend demonstriert er eine echtzeitfahige Erweiterung zur 2D/2C-Geschwindigkeitsmessung anhand eines 4x4-Sensor-Arrays. Zur inharenten ortsfilterbasierten Verarbeitung im optischen Pfad wurde ein Demonstrator basierend auf einem Mikro-Spiegel-Array realisiert."
The papers contained in this volume were presented at the Fourth Annual Symposium on Combinatorial Pattern Matching, held in Padova, Italy, in June 1993. Combinatorial pattern matching addresses issues of searching and matching of strings and more complicated patterns such as trees, regular expressions, extended expressions, etc. The goal is to derive nontrivial combinatorial properties for such structures and then to exploit these properties in order to achieve superior performance for the corresponding computational problems. In recent years, a steady flow of high-quality scientific studies of this subject has changed a sparse set of isolated results into a full-fledged area of algorithmics. The area is expected to grow even further due to the increasing demand for speedand efficiency that comes especially from molecular biology and the Genome project, but also from other diverse areas such as information retrieval, pattern recognition, compilers, data compression, and program analysis.
This volume contains the 22 papers accepted for presentation at the Third Annual Symposium on Combinatorial Pattern Matching held April 29 to May 1, 1992, in Tucson, Arizona; it constitutes the first conference proceedings entirely devoted to combinatorial pattern matching (CPM). CPM deals withissues of searching and matching of strings and other more complicated patterns such as trees, regular expressions, extended expressions, etc. in order to derive combinatorial properties for such structures. As an interdisciplinary field of growing interest, CPM is related to research in information retrieval, pattern recognition, compilers, data compression, and program analysis as well as to results, problems and methods from combinatorial mathematics and molecular biology.
This volume contains the papers selected for presentation at the Second International Conference on Parallel Image Analysis (ICPIA '92), held in Ube, Japan, December 21-23, 1992. The conference topics are data structures, parallel algorithms and architectures, neural networks, computational vision, syntactic generation and recognition, and multidimensional models. The first meeting with these topics was theInternational Colloquium on Parallel Image Processing, which took place in Paris in June 1991. The aim of the meetings is to bring together specialistsfrom various countries who are interested in the topics and to stimulatetheoretical and practical research in the field of parallel image processingand analysis. The volume contains three invited papers, a summary of a tutorial lecture, and twenty selected and refereed communications.
This book contains the 61 papers that were accepted for presenta tion at the 1992 British Machine Vision Conference. Together they provide a snapshot of current machine vision research throughout the UK in 24 different institutions. There are also several papers from vision groups in the rest of Europe, North America and Australia. At the start of the book is an invited paper from the first keynote speaker, Robert Haralick. The quality of papers submitted to the conference was very high and the programme committee had a hard task selecting around half for presentation at the meeting and inclusion in these proceedings. It is a positive feature of the annual BMV A conference that the entire process from the submission deadline through to the conference itself and publication of the proceedings is completed in under 5 months. My thanks to members of the programme committee for their essential contribution to the success of the conference and to Roger Boyle, Charlie Brown, Nick Efford and Sue Nemes for their excellent local organisation and administration of the conference at the University of Leeds."
This volume contains the papers from the first British Neural Network Society meeting held at Queen Elizabeth Hall, King's College, London on 18--20 April 1990. The meeting was sponsored by the London Mathemati cal Society. The papers include introductory tutorial lectures, invited, and contributed papers. The invited contributions were given by experts from the United States, Finland, Denmark, Germany and the United Kingdom. The majority of the contributed papers came from workers in the United Kingdom. The first day was devoted to tutorials. Professor Stephen Grossberg was a guest speaker on the first day giving a thorough introduction to his Adaptive Resonance Theory of neural networks. Subsequent tutorials on the first day covered dynamical systems and neural networks, realistic neural modelling, pattern recognition using neural networks, and a review of hardware for neural network simulations. The contributed papers, given on the second day, demonstrated the breadth of interests of workers in the field. They covered topics in pattern recognition, multi-layer feedforward neural networks, network dynamics, memory and learning. The ordering of the papers in this volume is as they were given at the meeting. On the final day talks were given by Professor Kohonen (on self organising maps), Professor Kurten (on the dynamics of random and structured nets) and Professor Cotterill (on modelling the visual cortex). Dr A. Mayes presented a paper on various models for amnesia. The editors have taken the opportunity to include a paper of their own which was not presented at the meeting."
This monograph is an outgrowth of the authors' recent research on the de velopment of algorithms for several low-level vision problems using artificial neural networks. Specific problems considered are static and motion stereo, computation of optical flow, and deblurring an image. From a mathematical point of view, these inverse problems are ill-posed according to Hadamard. Researchers in computer vision have taken the "regularization" approach to these problems, where one comes up with an appropriate energy or cost function and finds a minimum. Additional constraints such as smoothness, integrability of surfaces, and preservation of discontinuities are added to the cost function explicitly or implicitly. Depending on the nature of the inver sion to be performed and the constraints, the cost function could exhibit several minima. Optimization of such nonconvex functions can be quite involved. Although progress has been made in making techniques such as simulated annealing computationally more reasonable, it is our view that one can often find satisfactory solutions using deterministic optimization algorithms."
Software design patterns are known to play a vital role in enhancing the quality of software systems while reducing development time and cost. However, the use of these design patterns has also been known to introduce problems that can significantly reduce the stability, robustness, and reusability of software. This book introduces a new process for creating software design patterns that leads to highly stable, reusable, and cost-effective software. The basis of this new process is a topology of software patterns called knowledge maps. This book provides readers with a detailed view of the art and practice of creating meaningful knowledge maps. It demonstrates how to classify software patterns within knowledge maps according to their application rationale and nature. It provides readers with a clear methodology in the form of step-by-step guidelines, heuristics, and quality factors that simplify the process of creating knowledge maps. This book is designed to allow readers to master the basics of knowledge maps from their theoretical aspects to practical application. It begins with an overview of knowledge map concepts and moves on to knowledge map goals, capabilities, stable design patterns, development scenarios, and case studies. Each chapter of the book concludes with an open research issue, review questions, exercises, and a series of projects.
In this book a global shape model is developed and applied to the analysis of real pictures acquired with a visible light camera under varying conditions of optical degradation. Computational feasibility of the algorithms derived from this model is achieved by analytical means. The aim is to develop methods for image understanding based on structured restoration, for example automatic detection of abnormalities. We also want to find the limits of applicability of the algorithms. This is done by making the optical degradations more and more severe until the algorithms no longer succeed in their task. This computer experiment in pattern theory is one of several. The others, LEAVES, X-RAYS, and RANGE are described elsewhere. This book is suitable for an advanced undergraduate or graduate seminar in pattern theory, or as an accompanying book for applied probability, computer vision, or pattern recognition.
Mustererkennung heisst, ahnlich wie bei Sinneswahrnehmungen mit Sensoren Signale aus der technischen Umwelt zu empfangen und mit Hilfe zuvor gelernter Situationen momentane Messungen zu interpretieren und dabei im Hinblick auf neue Eindrucke lernfahig zu sein. Anlasslich des 11. DAGM-Symposiums wurden zu diesem Themenkomplex nahezu 100 Arbeiten eingereicht, von denen 42 Vortrage und 38 Plakatprasentationen zur Tagung und fur dieses Buch ausgewahlt wurden. Der Band enthalt Aufgabenstellungen, Denkweisen und neuere Forschungsergebnisse aus den Gebieten Mustererkennung, Bildverstehen, Bildfolgen, Wissensverarbeitung und Spracherkennung.
This book offers readers a broad view of research in some Western and Eastern European countries on pattern and signal analysis, and on coding, handling and measurement of images. It is a selection of refereed papers from two sources: first, a satellite conference within the biannual International Conference on Pattern Recognition held in Rome, November 14-17, 1988, and second, work done at the International Basic Laboratory on Image Processing and Computer Graphics, Berlin, GDR. The papers are grouped into three sections. The first section contains new proposals for the specific computation of particular features of digital images and the second section is devoted to the introduction and testing of general approaches to the solution of problems met in digital geometry, image coding, feature extraction and object classification. The third section illustrates some recent practical results obtained on real images specifically in character and speech recognition as well as in biomedicine. All the techniques illustrated in this book will find direct application in the near future. This book should interest and stimulate the reader, provoke new thoughts and encourage further research in this widely appealing field.
In this volume the author gives an introduction to the theory of group representations and their applications in image science. The main feature of the presentation is a systematic treatment of the invariance principle in image processing and pattern recognition with the help of group theoretical methods. The invariance properties of a problem often largely define the solution to the problem. Invariance principles are well known in theoretical physics but their use in image processing is only a few years old. The reader will find that group theory provides a unifying framework for many problems in image science. The volume is based on graduate-level lectures given by the author, and the book is intended for students and researchers interested in theoretical aspects of computer vision.
In this second edition every chapter of the first edition of Pattern Analysis has been updated and expanded. The general view of a system for pattern analysis and understanding has remained unchanged, but many details have been revised. A short account of light and sound has been added to the introduction, some normalization techniques and a basic introduction to morphological operations have been added to the second chapter. Chapter 3 has been expanded significantly by topics like motion, depth, and shape from shading; additional material has also been added to the already existing sections of this chapter. The old sections of Chap. 4 have been reorganized, a general view of the classification problem has been added and material provided to incorporate techniques of word and object recognition and to give a short account of some types of neural nets. Almost no changes have been made in Chap. 5. The part on representation of control structures in Chap. 6 has been shortened, a section on the judgement of results has been added. Chapter 7 has been rewritten almost completely; the section on formal grammars has been reduced, the sections on production systems, semantic networks, and knowledge acquisition have been expanded, and sections on logic and explanation added. The old Chaps. 8 and 9 have been omitted. In summary, the new edition is a thorough revision and extensive update of the first one taking into account the progress in the field during recent years.
Die 5. Osterreichische Artificial-Intelligence-Tagung setzt sich zusammen aus wissenschaftlichem Programm, Workshops und Tutorials. Der wissenschaftlich orientierte Teil des Tagungsprogramms umfasst sowohl eingeladene als auch begutachtete Vortrage zu den Themen Qualitatives Schliessen, Methodik Wissensbasierter Systeme und deren Anwendung, Logik/Deduktion, Naturlichsprachliche Systeme, Lernen und Kognition. Zum Informationsaustausch waren zusatzlich Workshops zur Weiterbildung vorgesehen. Besonders das Thema "Philosophie und KI" demonstrierte das allgemeine Interesse. Dies soll mit Beitragen dokumentiert werden, die einen Uberblick uber Beruhrungspunkte der KI mit philosophischen Stromungen bieten und auch den Einfluss der KI als Teil der Informatik auf das philosophische Weltbild verdeutlichen. Ebenfalls reprasentative Beitrage wurden zu den Workshops "Konnektionismus", "Qualitatives Schliessen" und "Begriffsbildung/-modellierung" ausgewahlt.
Pattern recognition is traditionally considered to cover all aspects of sensory data perception ranging from data acquisition, through preprocessing and low level analysis, to high level interpretation. Owing to its breadth and important application potential, the field of pattern recognition has been attracting considerable attention of researchers in academia and industry and consequently it has been witnessing a rapid growth and perpetual development. The need for dissemination of the latest results is being served by a host of international conferences on pattern recognition. One such series of meetings is regularly held in the United Kingdom under the auspices of the British Pattern Recognition Association. This volume contains papers presented at the BPRA 4th International Conference on Pattern Recognition held in Cambridge, March 28-30, 1988. Alongside the conventional topics of statistical and syntactic pattern recognition, contributions address issues in the hot subject areas of adaptive learning networks, computer vision, knowledge base methods and architectures for pattern processing, and among others, report progress in the application domains of document processing, speech and text recognition and shape analysis for industrial robotics. It is believed that the collection is not merely a report on current activities but that it will also be an important source of inspiration for future developments in the field of pattern recognition.
Das Buch fuhrt auf einfache und verstandliche Weise in die Bayes-Statistik ein. Ausgehend vom Bayes-Theorem werden die Schatzung unbekannter Parameter, die Festlegung von Konfidenzregionen fur die unbekannten Parameter und die Prufung von Hypothesen fur die Parameter abgeleitet. Angewendet werden die Verfahren fur die Parameterschatzung im linearen Modell, fur die Parameterschatzung, die sich robust gegenuber Ausreissern in den Beobachtungen verhalt, fur die Pradiktion und Filterung, die Varianz- und Kovarianzkomponentenschatzung und die Mustererkennung. Fur Entscheidungen in Systemen mit Unsicherheiten dienen Bayes-Netze. Lassen sich notwendige Integrale analytisch nicht losen, werden numerische Verfahren mit Hilfe von Zufallswerten eingesetzt." |
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