Pattern Recognition And Data Analysis With Applications

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Pattern Recognition and Data Analysis with Applications

Author : Deepak Gupta
Publisher : Springer Nature
ISBN 13 : 9811915202
Total Pages : 816 pages
Book Rating : 4.8/5 (119 download)

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Book Synopsis Pattern Recognition and Data Analysis with Applications by : Deepak Gupta

Download or read book Pattern Recognition and Data Analysis with Applications written by Deepak Gupta and published by Springer Nature. This book was released on 2022-09-01 with total page 816 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers latest advancements in the areas of machine learning, computer vision, pattern recognition, computational learning theory, big data analytics, network intelligence, signal processing and their applications in real world. The topics covered in machine learning involves feature extraction, variants of support vector machine (SVM), extreme learning machine (ELM), artificial neural network (ANN) and other areas in machine learning. The mathematical analysis of computer vision and pattern recognition involves the use of geometric techniques, scene understanding and modelling from video, 3D object recognition, localization and tracking, medical image analysis and so on. Computational learning theory involves different kinds of learning like incremental, online, reinforcement, manifold, multi-task, semi-supervised, etc. Further, it covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. Additionally, it covers the recent developments to network intelligence for analyzing the network information and thereby adapting the algorithms dynamically to improve the efficiency. In the last, it includes the progress in signal processing to process the normal and abnormal categories of real-world signals, for instance signals generated from IoT devices, smart systems, speech, videos, etc., and involves biomedical signal processing: electrocardiogram (ECG), electroencephalogram (EEG), magnetoencephalography (MEG) and electromyogram (EMG).

Data Analysis and Pattern Recognition in Multiple Databases

Author : Animesh Adhikari
Publisher : Springer Science & Business Media
ISBN 13 : 3319034103
Total Pages : 238 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Data Analysis and Pattern Recognition in Multiple Databases by : Animesh Adhikari

Download or read book Data Analysis and Pattern Recognition in Multiple Databases written by Animesh Adhikari and published by Springer Science & Business Media. This book was released on 2013-12-09 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types of data analyses are bound to change. Since the number of data collection channels increases in the recent time and becomes more diversified, many real-world data mining tasks can easily acquire multiple databases from various sources. In these cases, data mining becomes more challenging for several essential reasons. We may encounter sensitive data originating from different sources - those cannot be amalgamated. Even if we are allowed to place different data together, we are certainly not able to analyze them when local identities of patterns are required to be retained. Thus, pattern recognition in multiple databases gives rise to a suite of new, challenging problems different from those encountered before. Association rule mining, global pattern discovery and mining patterns of select items provide different patterns discovery techniques in multiple data sources. Some interesting item-based data analyses are also covered in this book. Interesting patterns, such as exceptional patterns, icebergs and periodic patterns have been recently reported. The book presents a thorough influence analysis between items in time-stamped databases. The recent research on mining multiple related databases is covered while some previous contributions to the area are highlighted and contrasted with the most recent developments.

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.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Author : Alvaro Pardo
Publisher : Springer
ISBN 13 : 9783319257501
Total Pages : 0 pages
Book Rating : 4.2/5 (575 download)

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Book Synopsis Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications by : Alvaro Pardo

Download or read book Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications written by Alvaro Pardo and published by Springer. This book was released on 2015-10-22 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 20th Iberoamerican Congress on Pattern Recognition, CIARP 2015, held in Montevideo, Uruguay, in November 2015. The 95 papers presented were carefully reviewed and selected from 185 submissions. The papers are organized in topical sections on applications on pattern recognition; biometrics; computer vision; gesture recognition; image classification and retrieval; image coding, processing and analysis; segmentation, analysis of shape and texture; signals analysis and processing; theory of pattern recognition; video analysis, segmentation and tracking.

Syntactic Pattern Recognition, Applications

Author : K.S. Fu
Publisher : Springer Science & Business Media
ISBN 13 : 3642664385
Total Pages : 278 pages
Book Rating : 4.6/5 (426 download)

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Book Synopsis Syntactic Pattern Recognition, Applications by : K.S. Fu

Download or read book Syntactic Pattern Recognition, Applications written by K.S. Fu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The many different mathematical techniques used to solve pattem recognition problems may be grouped into two general approaches: the decision-theoretic (or discriminant) approach and the syntactic (or structural) approach. In the decision-theoretic approach, aset of characteristic measurements, called features, are extracted from the pattems. Each pattem is represented by a feature vector, and the recognition of each pattem is usually made by partitioning the feature space. Applications of decision-theoretic approach indude character recognition, medical diagnosis, remote sensing, reliability and socio-economics. A relatively new approach is the syntactic approach. In the syntactic approach, ea ch pattem is expressed in terms of a composition of its components. The recognition of a pattem is usually made by analyzing the pattem structure according to a given set of rules. Earlier applications of the syntactic approach indude chromosome dassification, English character recognition and identification of bubble and spark chamber events. The purpose of this monograph is to provide a summary of the major reeent applications of syntactic pattem recognition. After a brief introduction of syntactic pattem recognition in Chapter 1, the nin e mai n chapters (Chapters 2-10) can be divided into three parts. The first three chapters concem with the analysis of waveforms using syntactic methods. Specific application examples indude peak detection and interpretation of electro cardiograms and the recognition of speech pattems. The next five chapters deal with the syntactic recognition of two-dimensional pictorial pattems.

Pattern Recognition

Author : J.P. Marques de Sá
Publisher : Springer Science & Business Media
ISBN 13 : 3642566510
Total Pages : 331 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis Pattern Recognition by : J.P. Marques de Sá

Download or read book Pattern Recognition written by J.P. Marques de Sá and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a comprehensive view of pattern recognition concepts and methods, illustrated with real-life applications in several areas. A CD-ROM offered with the book includes datasets and software tools, making it easier to follow in a hands-on fashion, right from the start.

Pattern Recognition and Image Analysis

Author : Earl Gose
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 504 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Pattern Recognition and Image Analysis by : Earl Gose

Download or read book Pattern Recognition and Image Analysis written by Earl Gose and published by Prentice Hall. This book was released on 1996 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past 20 to 25 years, pattern recognition has become an important part of image processing applications where the input data is an image. This book is a complete introduction to pattern recognition and its increasing role in image processing. It covers the traditional issues of pattern recognition and also introduces two of the fastest growing areas: Image Processing and Artificial Neural Networks. Examples and digital images illustrate the techniques, while an appendix describes pattern recognition using the SAS statistical software system.

Pattern Recognition And Big Data

Author : Pal Sankar Kumar
Publisher : World Scientific
ISBN 13 : 9813144564
Total Pages : 876 pages
Book Rating : 4.8/5 (131 download)

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Book Synopsis Pattern Recognition And Big Data by : Pal Sankar Kumar

Download or read book Pattern Recognition And Big Data written by Pal Sankar Kumar and published by World Scientific. This book was released on 2016-12-15 with total page 876 pages. Available in PDF, EPUB and Kindle. Book excerpt: Containing twenty six contributions by experts from all over the world, this book presents both research and review material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, linguistic, fuzzy-set-theoretic, neural, evolutionary computing and rough-set-theoretic to hybrid soft computing, with significant real-life applications. Pattern Recognition and Big Data provides state-of-the-art classical and modern approaches to pattern recognition and mining, with extensive real life applications. The book describes efficient soft and robust machine learning algorithms and granular computing techniques for data mining and knowledge discovery; and the issues associated with handling Big Data. Application domains considered include bioinformatics, cognitive machines (or machine mind developments), biometrics, computer vision, the e-nose, remote sensing and social network analysis.

Pattern Recognition Applications in Engineering

Author : Burgos, Diego Alexander Tibaduiza
Publisher : IGI Global
ISBN 13 : 1799818411
Total Pages : 357 pages
Book Rating : 4.7/5 (998 download)

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Book Synopsis Pattern Recognition Applications in Engineering by : Burgos, Diego Alexander Tibaduiza

Download or read book Pattern Recognition Applications in Engineering written by Burgos, Diego Alexander Tibaduiza and published by IGI Global. This book was released on 2019-12-27 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: The implementation of data and information analysis has become a trending solution within multiple professions. New tools and approaches are continually being developed within data analysis to further solve the challenges that come with professional strategy. Pattern recognition is an innovative method that provides comparison techniques and defines new characteristics within the information acquisition process. Despite its recent trend, a considerable amount of research regarding pattern recognition and its various strategies is lacking. Pattern Recognition Applications in Engineering is an essential reference source that discusses various strategies of pattern recognition algorithms within industrial and research applications and provides examples of results in different professional areas including electronics, computation, and health monitoring. Featuring research on topics such as condition monitoring, data normalization, and bio-inspired developments, this book is ideally designed for analysts; researchers; civil, mechanical, and electronic engineers; computing scientists; chemists; academicians; and students.

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

Applications of Pattern Recognition

Author : King-Sun Fu
Publisher : CRC Press
ISBN 13 : 1351086707
Total Pages : 392 pages
Book Rating : 4.3/5 (51 download)

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Book Synopsis Applications of Pattern Recognition by : King-Sun Fu

Download or read book Applications of Pattern Recognition written by King-Sun Fu and published by CRC Press. This book was released on 2019-07-22 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is intended to cover several major applications of pattern recognition. After a brief introduction to pattern recognition in Chapter 1, the two major approaches, statistical approach and syntactic approach, are reviewed in Chapter 2, and 3, respectively. Other topics include the application of pattern recognition to seismic wave interpretation, to system reliability problems, to medical data analysis, as well as character and speech recognition.

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.

Pattern Recognition Algorithms for Data Mining

Author : Sankar K. Pal
Publisher : CRC Press
ISBN 13 : 1135436401
Total Pages : 275 pages
Book Rating : 4.1/5 (354 download)

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Book Synopsis Pattern Recognition Algorithms for Data Mining by : Sankar K. Pal

Download or read book Pattern Recognition Algorithms for Data Mining written by Sankar K. Pal and published by CRC Press. This book was released on 2004-05-27 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern Recognition Algorithms for Data Mining addresses different pattern recognition (PR) tasks in a unified framework with both theoretical and experimental results. Tasks covered include data condensation, feature selection, case generation, clustering/classification, and rule generation and evaluation. This volume presents various theories, methodologies, and algorithms, using both classical approaches and hybrid paradigms. The authors emphasize large datasets with overlapping, intractable, or nonlinear boundary classes, and datasets that demonstrate granular computing in soft frameworks. Organized into eight chapters, the book begins with an introduction to PR, data mining, and knowledge discovery concepts. The authors analyze the tasks of multi-scale data condensation and dimensionality reduction, then explore the problem of learning with support vector machine (SVM). They conclude by highlighting the significance of granular computing for different mining tasks in a soft paradigm.

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.

Matrix Methods in Data Mining and Pattern Recognition

Author : Lars Elden
Publisher : SIAM
ISBN 13 : 0898716268
Total Pages : 226 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Matrix Methods in Data Mining and Pattern Recognition by : Lars Elden

Download or read book Matrix Methods in Data Mining and Pattern Recognition written by Lars Elden and published by SIAM. This book was released on 2007-07-12 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application.Matrix Methods in Data Mining and Pattern Recognition is divided into three parts. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB®. Some mathematical proofs that emphasize the existence and properties of the matrix decompositions are included. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed by the author are: classification of handwritten digits, text mining, text summarization, pagerank computations related to the GoogleÔ search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.Audience The book is intended for undergraduate students who have previously taken an introductory scientific computing/numerical analysis course. Graduate students in various data mining and pattern recognition areas who need an introduction to linear algebra techniques will also find the book useful.Contents Preface; Part I: Linear Algebra Concepts and Matrix Decompositions. Chapter 1: Vectors and Matrices in Data Mining and Pattern Recognition; Chapter 2: Vectors and Matrices; Chapter 3: Linear Systems and Least Squares; Chapter 4: Orthogonality; Chapter 5: QR Decomposition; Chapter 6: Singular Value Decomposition; Chapter 7: Reduced-Rank Least Squares Models; Chapter 8: Tensor Decomposition; Chapter 9: Clustering and Nonnegative Matrix Factorization; Part II: Data Mining Applications. Chapter 10: Classification of Handwritten Digits; Chapter 11: Text Mining; Chapter 12: Page Ranking for a Web Search Engine; Chapter 13: Automatic Key Word and Key Sentence Extraction; Chapter 14: Face Recognition Using Tensor SVD. Part III: Computing the Matrix Decompositions. Chapter 15: Computing Eigenvalues and Singular Values; Bibliography; Index.

Pattern Recognition

Author : S. Ramakrishnan
Publisher : BoD – Books on Demand
ISBN 13 : 9535128035
Total Pages : 137 pages
Book Rating : 4.5/5 (351 download)

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Book Synopsis Pattern Recognition by : S. Ramakrishnan

Download or read book Pattern Recognition written by S. Ramakrishnan and published by BoD – Books on Demand. This book was released on 2016-12-14 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: Pattern recognition continued to be one of the important research fields in computer science and electrical engineering. Lots of new applications are emerging, and hence pattern analysis and synthesis become significant subfields in pattern recognition. This book is an edited volume and has six chapters arranged into two sections, namely, pattern recognition analysis and pattern recognition applications. This book will be useful for graduate students, researchers, and practicing engineers working in the field of machine vision and computer science and engineering.

Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Author : João Manuel R. S. Tavares
Publisher : Springer
ISBN 13 : 9783030934194
Total Pages : 490 pages
Book Rating : 4.9/5 (341 download)

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Book Synopsis Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications by : João Manuel R. S. Tavares

Download or read book Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications written by João Manuel R. S. Tavares and published by Springer. This book was released on 2022-01-14 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 25th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2021, which took place during May 10–13, 2021. The conference was initially planned to take place in Porto, Portugal, but changed to a virtual event due to the COVID-19 pandemic. The 45 papers presented in this volume were carefully reviewed and selected from 82 submissions. They were organized in topical sections as follows: medical applications; natural language processing; metaheuristics; image segmentation; databases; deep learning; explainable artificial intelligence; image processing; machine learning; and computer vision.