Advances In Pattern Recognition

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Advances In Pattern Recognition And Artificial Intelligence

Author : Marleah Blom
Publisher : World Scientific
ISBN 13 : 9811239029
Total Pages : 277 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Advances In Pattern Recognition And Artificial Intelligence by : Marleah Blom

Download or read book Advances In Pattern Recognition And Artificial Intelligence written by Marleah Blom and published by World Scientific. This book was released on 2021-11-16 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes reviewed papers by international scholars from the 2020 International Conference on Pattern Recognition and Artificial Intelligence (held online). The papers have been expanded to provide more details specifically for the book. It is geared to promote ongoing interest and understanding about pattern recognition and artificial intelligence. Like the previous book in the series, this book covers a range of topics and illustrates potential areas where pattern recognition and artificial intelligence can be applied. It highlights, for example, how pattern recognition and artificial intelligence can be used to classify, predict, detect and help promote further discoveries related to credit scores, criminal news, national elections, license plates, gender, personality characteristics, health, and more.Chapters include works centred on medical and financial applications as well as topics related to handwriting analysis and text processing, internet security, image analysis, database creation, neural networks and deep learning. While the book is geared to promote interest from the general public, it may also be of interest to graduate students and researchers in the field.

Data Complexity in Pattern Recognition

Author : Mitra Basu
Publisher : Springer Science & Business Media
ISBN 13 : 1846281725
Total Pages : 309 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis Data Complexity in Pattern Recognition by : Mitra Basu

Download or read book Data Complexity in Pattern Recognition written by Mitra Basu and published by Springer Science & Business Media. This book was released on 2006-12-22 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic pattern recognition has uses in science and engineering, social sciences and finance. This book examines data complexity and its role in shaping theory and techniques across many disciplines, probing strengths and deficiencies of current classification techniques, and the algorithms that drive them. The book offers guidance on choosing pattern recognition classification techniques, and helps the reader set expectations for classification performance.

Advances in Pattern Recognition Research

Author : Thomas Lu
Publisher :
ISBN 13 : 9781536144291
Total Pages : 205 pages
Book Rating : 4.1/5 (442 download)

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Book Synopsis Advances in Pattern Recognition Research by : Thomas Lu

Download or read book Advances in Pattern Recognition Research written by Thomas Lu and published by . This book was released on 2018-11-16 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) has become a popular research topic recently. Pattern recognition (PR) is an important part of an AI system. If the AI is considered as the digital brain, then the PR is the visual and auditory cortex that converts the optical signals from the eyes and the acoustic signals from the ears to meaningful symbolic texts that the brain can digest. Over the past 40+ years, the processing speed of a digital computer has increased from kbits/s to tera floating point operations per second (TFLOPS), a 109 times acceleration. PR research has made significant advancements along the advancement of digital hardware, especially the graphical processing unit (GPU) technology that helps the rapid processing of complex images. In this book, the authors have collected the latest work from leading researchers in the PR fields. The topics are broad, which include optical implementation of various filters, digital implementation of state-of-the-art neural network (NN) training methods, and the latest deep leaning (DL) models. We also included applications of PR in various fields.

Advances in Pattern Recognition - ICAPR 2001

Author : Sameer Singh
Publisher : Springer
ISBN 13 : 3540447326
Total Pages : 482 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Advances in Pattern Recognition - ICAPR 2001 by : Sameer Singh

Download or read book Advances in Pattern Recognition - ICAPR 2001 written by Sameer Singh and published by Springer. This book was released on 2003-06-29 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation quality; Section 5 concludes this paper. 2. The norm-orientation-discontinuity interfering stroke model Figure 2 shows three typical samples of original image segments from the original documents and their magnitude of the detected edges respectively. The magnitude of the gradient is converted into the gray level value. The darker the edge is, the larger is the gradient magnitude. It is obvious that the topmost strong edges correspond to foreground edges. It should be noted that, while usually, the foreground writing appears darker than the background image, as shown in sample image Figure 2(a), there are cases where the foreground and background have similar intensities as shown in Figure 2(b), or worst still, the background is more prominent than the foreground as in Figure 2(c). So using only the intensity value is not enough to differentiate the foreground from the background. (a) (b) (c) (d) (e) (f)

Pattern Recognition by Self-organizing Neural Networks

Author : Gail A. Carpenter
Publisher : MIT Press
ISBN 13 : 9780262031769
Total Pages : 724 pages
Book Rating : 4.0/5 (317 download)

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Book Synopsis Pattern Recognition by Self-organizing Neural Networks by : Gail A. Carpenter

Download or read book Pattern Recognition by Self-organizing Neural Networks written by Gail A. Carpenter and published by MIT Press. This book was released on 1991 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern Recognition by Self-Organizing Neural Networks presentsthe most recent advances in an area of research that is becoming vitally important in the fields ofcognitive science, neuroscience, artificial intelligence, and neural networks in general. The 19articles take up developments in competitive learning and computational maps, adaptive resonancetheory, and specialized architectures and biological connections. Introductorysurvey articles provide a framework for understanding the many models involved in various approachesto studying neural networks. These are followed in Part 2 by articles that form the foundation formodels of competitive learning and computational mapping, and recent articles by Kohonen, applyingthem to problems in speech recognition, and by Hecht-Nielsen, applying them to problems in designingadaptive lookup tables. Articles in Part 3 focus on adaptive resonance theory (ART) networks,selforganizing pattern recognition systems whose top-down template feedback signals guarantee theirstable learning in response to arbitrary sequences of input patterns. In Part 4, articles describeembedding ART modules into larger architectures and provide experimental evidence fromneurophysiology, event-related potentials, and psychology that support the prediction that ARTmechanisms exist in the brain. Contributors: J.-P. Banquet, G.A. Carpenter, S.Grossberg, R. Hecht-Nielsen, T. Kohonen, B. Kosko, T.W. Ryan, N.A. Schmajuk, W. Singer, D. Stork, C.von der Malsburg, C.L. Winter.

Advanced Topics in Computer Vision

Author : Giovanni Maria Farinella
Publisher : Springer Science & Business Media
ISBN 13 : 1447155203
Total Pages : 433 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Advanced Topics in Computer Vision by : Giovanni Maria Farinella

Download or read book Advanced Topics in Computer Vision written by Giovanni Maria Farinella and published by Springer Science & Business Media. This book was released on 2013-09-24 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a broad selection of cutting-edge research, covering both theoretical and practical aspects of reconstruction, registration, and recognition. The text provides an overview of challenging areas and descriptions of novel algorithms. Features: investigates visual features, trajectory features, and stereo matching; reviews the main challenges of semi-supervised object recognition, and a novel method for human action categorization; presents a framework for the visual localization of MAVs, and for the use of moment constraints in convex shape optimization; examines solutions to the co-recognition problem, and distance-based classifiers for large-scale image classification; describes how the four-color theorem can be used for solving MRF problems; introduces a Bayesian generative model for understanding indoor environments, and a boosting approach for generalizing the k-NN rule; discusses the issue of scene-specific object detection, and an approach for making temporal super resolution video.

Advances In Pattern Recognition Systems Using Neural Network Technologies

Author : Patrick S P Wang
Publisher : World Scientific
ISBN 13 : 9814611816
Total Pages : 329 pages
Book Rating : 4.8/5 (146 download)

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Book Synopsis Advances In Pattern Recognition Systems Using Neural Network Technologies by : Patrick S P Wang

Download or read book Advances In Pattern Recognition Systems Using Neural Network Technologies written by Patrick S P Wang and published by World Scientific. This book was released on 1994-01-01 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents:A Connectionist Approach to Speech Recognition (Y Bengio)Signature Verification Using a “Siamese” Time Delay Neural Network (J Bromley et al.)Boosting Performance in Neural Networks (H Drucker et al.)An Integrated Architecture for Recognition of Totally Unconstrained Handwritten Numerals (A Gupta et al.)Time-Warping Network: A Neural Approach to Hidden Markov Model Based Speech Recognition (E Levin et al.)Computing Optical Flow with a Recurrent Neural Network (H Li & J Wang)Integrated Segmentation and Recognition through Exhaustive Scans or Learned Saccadic Jumps (G L Martin et al.)Experimental Comparison of the Effect of Order in Recurrent Neural Networks (C B Miller & C L Giles)Adaptive Classification by Neural Net Based Prototype Populations (K Peleg & U Ben-Hanan)A Neural System for the Recognition of Partially Occluded Objects in Cluttered Scenes: A Pilot Study (L Wiskott & C von der Malsburg)and other papers Readership: Computer scientists and engineers.

Pattern Recognition Technologies and Applications: Recent Advances

Author : Verma, Brijesh
Publisher : IGI Global
ISBN 13 : 1599048094
Total Pages : 454 pages
Book Rating : 4.5/5 (99 download)

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Book Synopsis Pattern Recognition Technologies and Applications: Recent Advances by : Verma, Brijesh

Download or read book Pattern Recognition Technologies and Applications: Recent Advances written by Verma, Brijesh and published by IGI Global. This book was released on 2008-06-30 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: The nature of handwriting in our society has significantly altered over the ages due to the introduction of new technologies such as computers and the World Wide Web. With increases in the amount of signature verification needs, state of the art internet and paper-based automated recognition methods are necessary. Pattern Recognition Technologies and Applications: Recent Advances provides cutting-edge pattern recognition techniques and applications. Written by world-renowned experts in their field, this easy to understand book is a must have for those seeking explanation in topics such as on- and offline handwriting and speech recognition, signature verification, and gender classification.

Pattern Recognition

Author : Sergios Theodoridis
Publisher : Elsevier
ISBN 13 : 9780080513621
Total Pages : 689 pages
Book Rating : 4.5/5 (136 download)

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Book Synopsis Pattern Recognition by : Sergios Theodoridis

Download or read book Pattern Recognition written by Sergios Theodoridis and published by Elsevier. This book was released on 2003-05-15 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms. *Approaches pattern recognition from the designer's point of view *New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere *Supplemented by computer examples selected from applications of interest

Pattern Recognition and Machine Learning

Author : Christopher M. Bishop
Publisher : Springer
ISBN 13 : 9781493938438
Total Pages : 0 pages
Book Rating : 4.9/5 (384 download)

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Book Synopsis Pattern Recognition and Machine Learning by : Christopher M. Bishop

Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Handbook Of Pattern Recognition And Computer Vision (2nd Edition)

Author : Chi Hau Chen
Publisher : World Scientific
ISBN 13 : 9814497649
Total Pages : 1045 pages
Book Rating : 4.8/5 (144 download)

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Book Synopsis Handbook Of Pattern Recognition And Computer Vision (2nd Edition) by : Chi Hau Chen

Download or read book Handbook Of Pattern Recognition And Computer Vision (2nd Edition) written by Chi Hau Chen and published by World Scientific. This book was released on 1999-03-12 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference. This indispensable handbook will continue to serve as an authoritative and comprehensive guide in the field.

Digital Pattern Recognition

Author : K. S. Fu
Publisher : Springer Science & Business Media
ISBN 13 : 364296303X
Total Pages : 217 pages
Book Rating : 4.6/5 (429 download)

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Book Synopsis Digital Pattern Recognition by : K. S. Fu

Download or read book Digital Pattern Recognition written by K. S. Fu and published by Springer Science & Business Media. This book was released on 2013-03-08 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: During the past fifteen years there has been a considerable growth of interest in problems of pattern recognition. Contributions to the blossom of this area have come from many disciplines, including statistics, psychology, linguistics, computer science, biology, taxonomy, switching theory, communication theory, control theory, and operations research. Many different approaches have been proposed and a number of books have been published. Most books published so far deal with the decision-theoretic (or statistical) approach or the syntactic (or linguistic) approach. Since the area of pattern recognition is still far from its maturity, many new research results, both in theory and in applications, are continuously produced. The purpose of this monograph is to provide a concise summary of the major recent developments in pattern recognition. The five main chapters (Chapter 2-6) in this book can be divided into two parts. The first three chapters concern primarily with basic techniques in pattern recognition. They include statistical techniques, clustering analysis and syntactic techniques. The last two chapters deal with applications; namely, picture recognition, and speech recognition and understanding. Each chapter is written by one or two distinguished experts on that subject. The editor has not attempted to impose upon the contributors to this volume a uniform notation and terminol ogy, since such notation and terminology does not as yet exist in pattern recognition.

Neural Networks for Pattern Recognition

Author : Christopher M. Bishop
Publisher : Oxford University Press
ISBN 13 : 0198538642
Total Pages : 501 pages
Book Rating : 4.1/5 (985 download)

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Book Synopsis Neural Networks for Pattern Recognition by : Christopher M. Bishop

Download or read book Neural Networks for Pattern Recognition written by Christopher M. Bishop and published by Oxford University Press. This book was released on 1995-11-23 with total page 501 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition; Probability density estimation; Single-layer networks; The multi-layer perceptron; Radial basis functions; Error functions; Parameter optimization algorithms; Pre-processing and feature extraction; Learning and generalization; Bayesian techniques; Appendix; References; Index.

Markov Models for Pattern Recognition

Author : Gernot A. Fink
Publisher : Springer Science & Business Media
ISBN 13 : 1447163087
Total Pages : 276 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Markov Models for Pattern Recognition by : Gernot A. Fink

Download or read book Markov Models for Pattern Recognition written by Gernot A. Fink and published by Springer Science & Business Media. This book was released on 2014-01-14 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly revised and expanded new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the perplexity measure and coverage of multi-pass decoding based on n-best search. Supporting the discussion of the theoretical foundations of Markov modeling, special emphasis is also placed on practical algorithmic solutions. Features: introduces the formal framework for Markov models; covers the robust handling of probability quantities; presents methods for the configuration of hidden Markov models for specific application areas; describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models; reviews key applications of Markov models.

Advanced Pattern Recognition Technologies with Applications to Biometrics

Author : David Zhang
Publisher : IGI Global
ISBN 13 :
Total Pages : 402 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Advanced Pattern Recognition Technologies with Applications to Biometrics by : David Zhang

Download or read book Advanced Pattern Recognition Technologies with Applications to Biometrics written by David Zhang and published by IGI Global. This book was released on 2009 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on two kinds of advanced biometric recognition technologies, biometric data discrimination and multi-biometrics"--Provided by publisher.

Pattern Recognition in Industry

Author : Phiroz Bhagat
Publisher : Elsevier
ISBN 13 : 9780080456027
Total Pages : 200 pages
Book Rating : 4.4/5 (56 download)

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Book Synopsis Pattern Recognition in Industry by : Phiroz Bhagat

Download or read book Pattern Recognition in Industry written by Phiroz Bhagat and published by Elsevier. This book was released on 2005-03-30 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?" If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build technical and business models to gain competitive industrial advantage. *Based on first-hand experience in the practice of pattern recognition technology and its development and deployment for profitable application in Industry. Phiroz Bhagat is often referred to as the pioneer of neural net and pattern recognition technology, and is uniquely qualified to write this book. He brings more than two decades of experience in the "real-world" application of cutting-edge technology for competitive advantage in industry. Two wave fronts are upon us today: we are being bombarded by an enormous amount of data, and we are confronted by continually increasing technical and business advances. Ideally, the endless stream of data should be one of our major assets. However, this potential asset often tends to overwhelm rather than enrich. Competitive advantage depends on our ability to extract and utilize nuggets of valuable knowledge and insight from this data deluge. The challenges that need to be overcome include the under-utilization of available data due to competing priorities, and the separate and somewhat disparate existing data systems that have difficulty interacting with each other. Conventional approaches to formulating models are becoming progressively more expensive in time and effort. To impart a competitive edge, engineering science in the 21st century needs to augment traditional modelling processes by auto-classifying and self-organizing data; developing models directly from operating experience, and then optimizing the results to provide effective strategies and operating decisions. This approach has wide applicability; in areas ranging from manufacturing processes, product performance and scientific research, to financial and business fields. This monograph explores pattern recognition technology, and its concomitant role in extracting useful knowledge to build technical and business models directly from data, and in optimizing the results derived from these models within the context of delivering competitive industrial advantage. It is not intended to serve as a comprehensive reference source on the subject. Rather, it is based on first-hand experience in the practice of this technology: its development and deployment for profitable application in industry. The technical topics covered in the monograph will focus on the triad of technological areas that constitute the contemporary workhorses of successful industrial application of pattern recognition. These are: systems for self-organising data; data-driven modelling; and genetic algorithms as robust optimizers. "Find it hard to extract and utilise valuable knowledge from the ever-increasing data deluge?" If so, this book will help, as it explores pattern recognition technology and its concomitant role in extracting useful information to build technical and business models to gain competitive industrial advantage. Based on first-hand experience in the practice of pattern recognition technology and its development and deployment for profitable application in Industry. Phiroz Bhagat is often referred to as the pioneer of neural net and pattern recognition technology, and is uniquely qualified to write this book. He brings more than two decades of experience in the "real-world" application of cutting-edge technology for competitive advantage in industry.

Statistical Pattern Recognition

Author : Andrew R. Webb
Publisher : John Wiley & Sons
ISBN 13 : 0470854782
Total Pages : 516 pages
Book Rating : 4.4/5 (78 download)

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Book Synopsis Statistical Pattern Recognition by : Andrew R. Webb

Download or read book Statistical Pattern Recognition written by Andrew R. Webb and published by John Wiley & Sons. This book was released on 2003-07-25 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical pattern recognition is a very active area of study andresearch, which has seen many advances in recent years. New andemerging applications - such as data mining, web searching,multimedia data retrieval, face recognition, and cursivehandwriting recognition - require robust and efficient patternrecognition techniques. Statistical decision making and estimationare regarded as fundamental to the study of pattern recognition. Statistical Pattern Recognition, Second Edition has been fullyupdated with new methods, applications and references. It providesa comprehensive introduction to this vibrant area - with materialdrawn from engineering, statistics, computer science and the socialsciences - and covers many application areas, such as databasedesign, artificial neural networks, and decision supportsystems. * Provides a self-contained introduction to statistical patternrecognition. * Each technique described is illustrated by real examples. * Covers Bayesian methods, neural networks, support vectormachines, and unsupervised classification. * Each section concludes with a description of the applicationsthat have been addressed and with further developments of thetheory. * Includes background material on dissimilarity, parameterestimation, data, linear algebra and probability. * Features a variety of exercises, from 'open-book' questions tomore lengthy projects. The book is aimed primarily at senior undergraduate and graduatestudents studying statistical pattern recognition, patternprocessing, neural networks, and data mining, in both statisticsand engineering departments. It is also an excellent source ofreference for technical professionals working in advancedinformation development environments. For further information on the techniques and applicationsdiscussed in this book please visit ahref="http://www.statistical-pattern-recognition.net/"www.statistical-pattern-recognition.net/a