pattern recognition and classification

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Pattern Recognition And Classification

Author : Geoff Dougherty
ISBN : 9781461453239
Genre : Computers
File Size : 77. 7 MB
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The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer vision. Fundamental concepts of supervised and unsupervised classification are presented in an informal, rather than axiomatic, treatment so that the reader can quickly acquire the necessary background for applying the concepts to real problems. More advanced topics, such as semi-supervised classification, combining clustering algorithms and relevance feedback are addressed in the later chapters. This book is suitable for undergraduates and graduates studying pattern recognition and machine learning.

Pattern Recognition And Classification In Time Series Data

Author : Volna, Eva
ISBN : 9781522505662
Genre : Computers
File Size : 53. 35 MB
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Patterns can be any number of items that occur repeatedly, whether in the behaviour of animals, humans, traffic, or even in the appearance of a design. As technologies continue to advance, recognizing, mimicking, and responding to all types of patterns becomes more precise. Pattern Recognition and Classification in Time Series Data focuses on intelligent methods and techniques for recognizing and storing dynamic patterns. Emphasizing topics related to artificial intelligence, pattern management, and algorithm development, in addition to practical examples and applications, this publication is an essential reference source for graduate students, researchers, and professionals in a variety of computer-related disciplines.

Invariants For Pattern Recognition And Classification

Author : Marcos A Rodrigues
ISBN : 9789814493277
Genre : Computers
File Size : 50. 41 MB
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This book was conceived from the realization that there was a need to update recent work on invariants in a single volume providing a useful set of references and pointers to related work. Since the publication in 1992 of J L Mundy and A Zisserman's Geometric Invariance in Computer Vision, the subject has been evolving rapidly. New approaches to invariants have been proposed and novel ways of defining and applying invariants to practical problem solving are testimony to the fundamental importance of the study of invariants to machine vision. This book represents a snapshot of current research around the world. A version of this collection of papers has appeared in the International Journal of Pattern Recognition and Artificial Intelligence (December 1999). The papers in this book are extended versions of the original material published in the journal. They are organized into two categories: foundations and applications. Foundation papers present new ways of defining or analyzing invariants, and application papers present novel ways in which known invariant theory is extended and effectively applied to real-world problems in interesting and difficult contexts. Each category contains roughly half of the papers, but there is considerable overlap. All papers carry an element of novelty and generalization that will be useful to theoreticians and practitioners alike. It is hoped that this volume will be not only useful but also inspirational to researchers in image processing, pattern recognition and computer vision at large. Contents:Analysis and Computation of Projective Invariants from Multiple Views in the Geometric Algebra FrameworkInvariants to Convolution and RotationA New Representation for Quartic Curves and Complete Sets of Geometric InvariantsA Robust Affine Invariant Metric on Boundary PatternsInvariant Geometric Properties of Image Correspondence Vectors as Rigid Constraints to Motion EstimationFeatures of Derivative Continuity in ShapeFourier–Mellin Based Invariants for the Recognition of Multi-Oriented and Multi-Scaled Shapes — Application to Engineering Drawing AnalysisHigh-Order Statistical Pattern Spectrum: An Invariant and Noise-Robust Shape DescriptorImproved Moment Invariants for Invariant Image RepresentationAn Approach Using Elastic Graph Dynamic Link Model for Automating the Satellite Interpretation of Tropical Cyclone PatternsColour Normalization for Colour Object Recognition and Image Retrieval Readership: Researchers in pattern recognition and computer vision. Keywords:Calibration;Motion Estimation;Image Registration;Quartic Curves;Affine Invariants;Moment Invariants;Complex Moments;Document Interpretation;Projective Geometry;Geometric Algebra;Fourier-Mellin Transform;Active Contour Model;Color Normalization;Shape Modeling

Neural Networks Using Matlab

Author : K. Taylor
ISBN : 1543065325
Genre :
File Size : 61. 27 MB
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MATLAB has the tool Neural Network Toolbox that provides algorithms, functions, and apps to create, train, visualize, and simulate neural networks. You can perform classification, regression, clustering, dimensionality reduction, time-series forecasting, and dynamic system modeling and control. The toolbox includes convolutional neural network and autoencoder deep learning algorithms for image classification and feature learning tasks. To speed up training of large data sets, you can distribute computations and data across multicore processors, GPUs, and computer clusters using Parallel Computing Toolbox. The more important features are the following: -Deep learning, including convolutional neural networks and autoencoders -Parallel computing and GPU support for accelerating training (with Parallel Computing Toolbox) -Supervised learning algorithms, including multilayer, radial basis, learning vector quantization (LVQ), time-delay, nonlinear autoregressive (NARX), and recurrent neural network (RNN) -Unsupervised learning algorithms, including self-organizing maps and competitive layers -Apps for data-fitting, pattern recognition, and clustering -Preprocessing, postprocessing, and network visualization for improving training efficiency and assessing network performance -Simulink blocks for building and evaluating neural networks and for control systems applications This book especially develops the applications of the neural networks to the classification and the patterns recognition

Classification Pattern Recognition And Reduction Of Dimensionality

Author : Paruchuri R. Krishnaiah
ISBN : 044486217X
Genre : Mathematics
File Size : 68. 53 MB
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Discriminant analysis for time series; Optimum rules for classification into two multivariate normal populations with the same covariance matrix;Large sample approximations and asymptotic expansions of classification statistics; Bayesian discrimination; Classification of growth curves; Nonparametric classification; Logistic discrimination; Nearest neighbor methods in discrimination; The classification and mixture maximum likelihood approaches to cluster analysis; Graphical techniques for multivariate data and for clustering; Cluster analysis software; Single-link clustering algorithms; Theory of multidimensional scaling; Multidimensional scaling and its applications; Intrinsic dimensionality extraction; Intrinsic dimensionality extraction; Structural methods in image analysis and recognition; Image models; Image texture survey; Applications of stochastic languages; A unifying viewpoint on pattern recognition; Logical functions in the problems of empirical prediction; Inference and data tables with missing values; Recognition of electrocardiographic patterns; Waveform parsing systems...

Classification Estimation And Pattern Recognition

Author : Tzay Y. Young
ISBN : 0444001352
Genre : Psychology
File Size : 49. 18 MB
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Introduction To Pattern Recognition

Author : Menahem Friedman
ISBN : 9789813105188
Genre : Computers
File Size : 73. 59 MB
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This book is an introduction to pattern recognition, meant for undergraduate and graduate students in computer science and related fields in science and technology. Most of the topics are accompanied by detailed algorithms and real world applications. In addition to statistical and structural approaches, novel topics such as fuzzy pattern recognition and pattern recognition via neural networks are also reviewed. Each topic is followed by several examples solved in detail. The only prerequisites for using this book are a one-semester course in discrete mathematics and a knowledge of the basic preliminaries of calculus, linear algebra and probability theory.

Image Recognition And Classification

Author : Bahram Javidi
ISBN : 0203910966
Genre : Technology & Engineering
File Size : 72. 39 MB
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"Details the latest image processing algorithms and imaging systems for image recognition with diverse applications to the military; the transportation, aerospace, information security, and biomedical industries; radar systems; and image tracking systems."

Artificial Intelligence In Recognition And Classification Of Astrophysical And Medical Images

Author : Valentina Zharkova
ISBN : 9783540475187
Genre : Mathematics
File Size : 41. 59 MB
Format : PDF
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This book presents innovative techniques in recognition and classification of astrophysical and medical images. Coverage includes: image standardization and enhancement; region-based methods for pattern recognition in medical and astrophysical images; advanced information processing using statistical methods; and feature recognition and classification using spectral method.

Pattern Recognition And Classification Approach To Pre Processing Arterial Pressure Waveform Signals And Image Processing Problems

Author : Leonid B. Volfson
ISBN : UCSD:31822003558749
Genre :
File Size : 31. 17 MB
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