Rough Fuzzy Pattern Recognition

Download Rough Fuzzy Pattern Recognition full books in PDF, epub, and Kindle. Read online Rough Fuzzy Pattern Recognition ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Rough-Fuzzy Pattern Recognition

Author : Pradipta Maji
Publisher : John Wiley & Sons
ISBN 13 : 111800440X
Total Pages : 312 pages
Book Rating : 4.1/5 (18 download)

DOWNLOAD NOW!

Book Synopsis Rough-Fuzzy Pattern Recognition by : Pradipta Maji

Download or read book Rough-Fuzzy Pattern Recognition written by Pradipta Maji and published by John Wiley & Sons. This book was released on 2012-02-14 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to apply rough-fuzzy computing techniques to solve problems in bioinformatics and medical image processing Emphasizing applications in bioinformatics and medical image processing, this text offers a clear framework that enables readers to take advantage of the latest rough-fuzzy computing techniques to build working pattern recognition models. The authors explain step by step how to integrate rough sets with fuzzy sets in order to best manage the uncertainties in mining large data sets. Chapters are logically organized according to the major phases of pattern recognition systems development, making it easier to master such tasks as classification, clustering, and feature selection. Rough-Fuzzy Pattern Recognition examines the important underlying theory as well as algorithms and applications, helping readers see the connections between theory and practice. The first chapter provides an introduction to pattern recognition and data mining, including the key challenges of working with high-dimensional, real-life data sets. Next, the authors explore such topics and issues as: Soft computing in pattern recognition and data mining A mathematical framework for generalized rough sets, incorporating the concept of fuzziness in defining the granules as well as the set Selection of non-redundant and relevant features of real-valued data sets Selection of the minimum set of basis strings with maximum information for amino acid sequence analysis Segmentation of brain MR images for visualization of human tissues Numerous examples and case studies help readers better understand how pattern recognition models are developed and used in practice. This text—covering the latest findings as well as directions for future research—is recommended for both students and practitioners working in systems design, pattern recognition, image analysis, data mining, bioinformatics, soft computing, and computational intelligence.

Rough Fuzzy Image Analysis

Author : Sankar K. Pal
Publisher : CRC Press
ISBN 13 : 9781439803301
Total Pages : 266 pages
Book Rating : 4.8/5 (33 download)

DOWNLOAD NOW!

Book Synopsis Rough Fuzzy Image Analysis by : Sankar K. Pal

Download or read book Rough Fuzzy Image Analysis written by Sankar K. Pal and published by CRC Press. This book was released on 2010-05-04 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy sets, near sets, and rough sets are useful and important stepping stones in a variety of approaches to image analysis. These three types of sets and their various hybridizations provide powerful frameworks for image analysis. Emphasizing the utility of fuzzy, near, and rough sets in image analysis, Rough Fuzzy Image Analysis: Foundations and Methodologies introduces the fundamentals and applications in the state of the art of rough fuzzy image analysis. In the first chapter, the distinguished editors explain how fuzzy, near, and rough sets provide the basis for the stages of pictorial pattern recognition: image transformation, feature extraction, and classification. The text then discusses hybrid approaches that combine fuzzy sets and rough sets in image analysis, illustrates how to perform image analysis using only rough sets, and describes tolerance spaces and a perceptual systems approach to image analysis. It also presents a free, downloadable implementation of near sets using the Near Set Evaluation and Recognition (NEAR) system, which visualizes concepts from near set theory. In addition, the book covers an array of applications, particularly in medical imaging involving breast cancer diagnosis, laryngeal pathology diagnosis, and brain MR segmentation. Edited by two leading researchers and with contributions from some of the best in the field, this volume fully reflects the diversity and richness of rough fuzzy image analysis. It deftly examines the underlying set theories as well as the diverse methods and applications.

Neuro-Fuzzy Pattern Recognition

Author : Sankar K. Pal
Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 418 pages
Book Rating : 4.3/5 (91 download)

DOWNLOAD NOW!

Book Synopsis Neuro-Fuzzy Pattern Recognition by : Sankar K. Pal

Download or read book Neuro-Fuzzy Pattern Recognition written by Sankar K. Pal and published by Wiley-Interscience. This book was released on 1999 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: The neuro-fuzzy approach to pattern recognition-a unique overview Recent years have seen a surge of interest in neuro-fuzzy computing, which combines fuzzy logic, neural networks, and soft computing techniques. This book focuses on the application of this new tool to the rapidly evolving area of pattern recognition. Written by two leaders in neural networks and soft computing research, this landmark work presents a unified, comprehensive treatment of the state of the art in the field. The authors consolidate a wealth of information previously cattered in disparate articles, journals, and edited volumes, explaining both the theory of neuro-fuzzy computing and the latest methodologies for performing different pattern recognition tasks in the neuro-fuzzy network-classification, feature evaluation, rule generation, knowledge extraction, and hybridization. Special emphasis is given to the integration of neuro-fuzzy methods with rough sets and genetic algorithms (GAs) to ensure more efficient recognition systems. Clear, concise, and fully referenced, Neuro-Fuzzy Pattern Recognition features extensive examples and highlights key applications in speech, machine learning, medicine, and forensic science. It is an extremely useful resource for scientists and engineers in laboratories and industry as well as for anyone seeking up-to-date information on the advantages of neuro-fuzzy pattern recognition in new computer technologies.

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)

DOWNLOAD NOW!

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.

Fuzzy Algorithms: With Applications To Image Processing And Pattern Recognition

Author : Zheru Chi
Publisher : World Scientific
ISBN 13 : 9814498858
Total Pages : 239 pages
Book Rating : 4.8/5 (144 download)

DOWNLOAD NOW!

Book Synopsis Fuzzy Algorithms: With Applications To Image Processing And Pattern Recognition by : Zheru Chi

Download or read book Fuzzy Algorithms: With Applications To Image Processing And Pattern Recognition written by Zheru Chi and published by World Scientific. This book was released on 1996-10-04 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents:Introduction:Basic Concepts of Fuzzy SetsFuzzy RelationsFuzzy Models for Image Processing and Pattern RecognitionMembership Functions:IntroductionHeuristic SelectionsClustering ApproachesTuning of Membership FunctionsConcluding RemarksOptimal Image Thresholding:IntroductionThreshold Selection Based on Statistical Decision TheoryNon-fuzzy Thresholding AlgorithmsFuzzy Thresholding AlgorithmUnified Formulation of Three Thresholding AlgorithmsMultilevel ThresholdingApplicationsConcluding RemarksFuzzy Clustering:IntroductionC-Means AlgorithmFuzzy C-Means AlgorithmComparison between Hard and Fuzzy Clustering AlgorithmsCluster ValidityApplicationsConcluding RemarksLine Pattern Matching:IntroductionSimilarity Measures between Line SegmentsBasic Matching AlgorithmDealing with Noisy PatternsDealing with Rotated PatternsApplicationsConcluding RemarksFuzzy Rule-based Systems:IntroductionLearning from ExamplesDecision Tree ApproachFuzzy Aggregation Network ApproachMinimization of Fuzzy RulesDefuzzification and OptimizationApplicationsConcluding RemarksCombined Classifiers:IntroductionVoting SchemesMaximum Posteriori ProbabilityMultilayer Perceptron ApproachFuzzy Measures and Fuzzy IntegralsApplicationsConcluding Remarks Readership: Engineers and computer scientists. keywords:

Granular Neural Networks, Pattern Recognition and Bioinformatics

Author : Sankar K. Pal
Publisher : Springer
ISBN 13 : 331957115X
Total Pages : 227 pages
Book Rating : 4.3/5 (195 download)

DOWNLOAD NOW!

Book Synopsis Granular Neural Networks, Pattern Recognition and Bioinformatics by : Sankar K. Pal

Download or read book Granular Neural Networks, Pattern Recognition and Bioinformatics written by Sankar K. Pal and published by Springer. This book was released on 2017-05-02 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,. The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinformatics applications. The book is recommended for both students and practitioners working in computer science, electrical engineering, data science, system design, pattern recognition, image analysis, neural computing, social network analysis, big data analytics, computational biology and soft computing.

Soft Computing Approach to Pattern Recognition and Image Processing

Author : Ashish Ghosh
Publisher : World Scientific
ISBN 13 : 9789812776235
Total Pages : 374 pages
Book Rating : 4.7/5 (762 download)

DOWNLOAD NOW!

Book Synopsis Soft Computing Approach to Pattern Recognition and Image Processing by : Ashish Ghosh

Download or read book Soft Computing Approach to Pattern Recognition and Image Processing written by Ashish Ghosh and published by World Scientific. This book was released on 2002 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume provides a collection of sixteen articles containing review and new material. In a unified way, they describe the recent development of theories and methodologies in pattern recognition, image processing and vision using fuzzy logic, artificial neural networks, genetic algorithms, rough sets and wavelets with significant real life applications. The book details the theory of granular computing and the role of a rough-neuro approach as a way of computing with words and designing intelligent recognition systems. It also demonstrates applications of the soft computing paradigm to case based reasoning, data mining and bio-informatics with a scope for future research. The contributors from around the world present a balanced mixture of current theory, algorithms and applications, making the book an extremely useful resource for students and researchers alike. Contents: Pattern Recognition: Multiple Classifier Systems; Building Decision Trees from the Fourier Spectrum of a Tree Ensemble; Clustering Large Data Sets; Multi-objective Variable String Genetic Classifier: Application to Remote Sensing Imagery; Image Processing and Vision: Dissimilarity Measures Between Fuzzy Sets or Fuzzy Structures; Early Vision: Concepts and Algorithms; Self-organizing Neural Network for Multi-level Image Segmentation; Geometric Transformation by Moment Method with Wavelet Matrix; New Computationally Efficient Algorithms for Video Coding; Soft Computing for Computational Media Aesthetics: Analyzing Video Content for Meaning; Granular Computing and Case Based Reasoning: Towards Granular Multi-agent Systems; Granular Computing and Pattern Recognition; Case Base Maintenance: A Soft Computing Perspective; Real Life Applications: Autoassociative Neural Network Models for Pattern Recognition Tasks in Speech and Image; Protein Structure Prediction Using Soft Computing; Pattern Classification for Biological Data Mining. Readership: Upper level undergraduates, graduates, researchers, academics and industrialists.

Scalable Pattern Recognition Algorithms

Author : Pradipta Maji
Publisher : Springer Science & Business Media
ISBN 13 : 3319056301
Total Pages : 316 pages
Book Rating : 4.3/5 (19 download)

DOWNLOAD NOW!

Book Synopsis Scalable Pattern Recognition Algorithms by : Pradipta Maji

Download or read book Scalable Pattern Recognition Algorithms written by Pradipta Maji and published by Springer Science & Business Media. This book was released on 2014-03-19 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.

Neuro-fuzzy Pattern Recognition

Author : Horst Bunke
Publisher : World Scientific
ISBN 13 : 9810244185
Total Pages : 276 pages
Book Rating : 4.8/5 (12 download)

DOWNLOAD NOW!

Book Synopsis Neuro-fuzzy Pattern Recognition by : Horst Bunke

Download or read book Neuro-fuzzy Pattern Recognition written by Horst Bunke and published by World Scientific. This book was released on 2000 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks and fuzzy techniques are among the most promising approaches to pattern recognition. Neuro-fuzzy systems aim at combining the advantages of the two paradigms. This book is a collection of papers describing state-of-the-art work in this emerging field. It covers topics such as feature selection, classification, classifier training, and clustering. Also included are applications of neuro-fuzzy systems in speech recognition, land mine detection, medical image analysis, and autonomous vehicle control. The intended audience includes graduate students in computer science and related fields, as well as researchers at academic institutions and in industry.

Computational Intelligence in Multi-Feature Visual Pattern Recognition

Author : Pramod Kumar Pisharady
Publisher : Springer
ISBN 13 : 9812870563
Total Pages : 138 pages
Book Rating : 4.8/5 (128 download)

DOWNLOAD NOW!

Book Synopsis Computational Intelligence in Multi-Feature Visual Pattern Recognition by : Pramod Kumar Pisharady

Download or read book Computational Intelligence in Multi-Feature Visual Pattern Recognition written by Pramod Kumar Pisharady and published by Springer. This book was released on 2014-05-23 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good inter class discrimination. A Bayesian model of visual attention is described which is effective in handling complex background problem in hand posture recognition. The book provides qualitative and quantitative performance comparisons for the algorithms outlined, with other standard methods in machine learning and computer vision. The book is self-contained with several figures, charts, tables and equations helping the reader to understand the material presented without instruction.

Rough Sets, Fuzzy Sets and Knowledge Discovery

Author : Wojciech P. Ziarko
Publisher : Springer Science & Business Media
ISBN 13 : 1447132386
Total Pages : 486 pages
Book Rating : 4.4/5 (471 download)

DOWNLOAD NOW!

Book Synopsis Rough Sets, Fuzzy Sets and Knowledge Discovery by : Wojciech P. Ziarko

Download or read book Rough Sets, Fuzzy Sets and Knowledge Discovery written by Wojciech P. Ziarko and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this book is two-fold. Firstly, it is aimed at bringing to gether key research articles concerned with methodologies for knowledge discovery in databases and their applications. Secondly, it also contains articles discussing fundamentals of rough sets and their relationship to fuzzy sets, machine learning, management of uncertainty and systems of logic for formal reasoning about knowledge. Applications of rough sets in different areas such as medicine, logic design, image processing and expert systems are also represented. The articles included in the book are based on selected papers presented at the International Workshop on Rough Sets and Knowledge Discovery held in Banff, Canada in 1993. The primary methodological approach emphasized in the book is the mathematical theory of rough sets, a relatively new branch of mathematics concerned with the modeling and analysis of classification problems with imprecise, uncertain, or incomplete information. The methods of the theory of rough sets have applications in many sub-areas of artificial intelligence including knowledge discovery, machine learning, formal reasoning in the presence of uncertainty, knowledge acquisition, and others. This spectrum of applications is reflected in this book where articles, although centered around knowledge discovery problems, touch a number of related issues. The book is intended to provide an important reference material for students, researchers, and developers working in the areas of knowledge discovery, machine learning, reasoning with uncertainty, adaptive expert systems, and pattern classification.

Rough-Neural Computing

Author : Sankar Kumar Pal
Publisher : Springer Science & Business Media
ISBN 13 : 3642188591
Total Pages : 741 pages
Book Rating : 4.6/5 (421 download)

DOWNLOAD NOW!

Book Synopsis Rough-Neural Computing by : Sankar Kumar Pal

Download or read book Rough-Neural Computing written by Sankar Kumar Pal and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 741 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soft computing comprises various paradigms dedicated to approximately solving real-world problems, e.g. in decision making, classification or learning; among these paradigms are fuzzy sets, rough sets, neural networks, genetic algorithms, and others. It is well understood now in the soft computing community that hybrid approaches combining various paradigms are very promising approaches for solving complex problems. Exploiting the potential and strength of both neural networks and rough sets, this book is devoted to rough-neuro computing which is also related to the novel aspect of computing based on information granulation, in particular to computing with words. It provides foundational and methodological issues as well as applications in various fields.

Pattern Recognition and Machine Intelligence

Author : Marzena Kryszkiewicz
Publisher : Springer
ISBN 13 : 3319199412
Total Pages : 588 pages
Book Rating : 4.3/5 (191 download)

DOWNLOAD NOW!

Book Synopsis Pattern Recognition and Machine Intelligence by : Marzena Kryszkiewicz

Download or read book Pattern Recognition and Machine Intelligence written by Marzena Kryszkiewicz and published by Springer. This book was released on 2015-06-22 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 6th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2015, held in Warsaw, Poland, in June/July 2015. The total of 53 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 90 submissions. They were organized in topical sections named: foundations of machine learning; image processing; image retrieval; image tracking; pattern recognition; data mining techniques for large scale data; fuzzy computing; rough sets; bioinformatics; and applications of artificial intelligence.

Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing

Author : Guoyin Wang
Publisher : Springer
ISBN 13 : 354039205X
Total Pages : 746 pages
Book Rating : 4.5/5 (43 download)

DOWNLOAD NOW!

Book Synopsis Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing by : Guoyin Wang

Download or read book Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing written by Guoyin Wang and published by Springer. This book was released on 2003-08-03 with total page 746 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers selected for presentation at the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2003) held at Chongqing University of Posts and Telecommunications, Chongqing, P.R. China, May 26–29, 2003. There were 245 submissions for RSFDGrC 2003 excluding for 2 invited keynote papers and 11 invited plenary papers. Apart from the 13 invited papers, 114 papers were accepted for RSFDGrC 2003 and were included in this volume. The acceptance rate was only 46.5%. These papers were divided into 39 regular oral presentation papers (each allotted 8 pages), 47 short oral presentation papers (each allotted 4 pages) and 28 poster presentation papers (each allotted 4 pages) on the basis of reviewer evaluations. Each paper was reviewed by three referees. The conference is a continuation and expansion of the International Workshops on Rough Set Theory and Applications. In particular, this was the ninth meeting in the series and the first international conference. The aim of RSFDGrC2003 was to bring together researchers from diverse fields of expertise in order to facilitate mutual understanding and cooperation and to help in cooperative work aimed at new hybrid paradigms. It is our great pleasure to dedicate this volume to Prof. Zdzislaw Pawlak, who first introduced the basic ideas and definitions of rough sets theory over 20 years ago.

Pattern Recognition with Fuzzy Objective Function Algorithms

Author : James C. Bezdek
Publisher : Springer Science & Business Media
ISBN 13 : 147570450X
Total Pages : 267 pages
Book Rating : 4.4/5 (757 download)

DOWNLOAD NOW!

Book Synopsis Pattern Recognition with Fuzzy Objective Function Algorithms by : James C. Bezdek

Download or read book Pattern Recognition with Fuzzy Objective Function Algorithms written by James C. Bezdek and published by Springer Science & Business Media. This book was released on 2013-03-13 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fuzzy set was conceived as a result of an attempt to come to grips with the problem of pattern recognition in the context of imprecisely defined categories. In such cases, the belonging of an object to a class is a matter of degree, as is the question of whether or not a group of objects form a cluster. A pioneering application of the theory of fuzzy sets to cluster analysis was made in 1969 by Ruspini. It was not until 1973, however, when the appearance of the work by Dunn and Bezdek on the Fuzzy ISODATA (or fuzzy c-means) algorithms became a landmark in the theory of cluster analysis, that the relevance of the theory of fuzzy sets to cluster analysis and pattern recognition became clearly established. Since then, the theory of fuzzy clustering has developed rapidly and fruitfully, with the author of the present monograph contributing a major share of what we know today. In their seminal work, Bezdek and Dunn have introduced the basic idea of determining the fuzzy clusters by minimizing an appropriately defined functional, and have derived iterative algorithms for computing the membership functions for the clusters in question. The important issue of convergence of such algorithms has become much better understood as a result of recent work which is described in the monograph.

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)

DOWNLOAD NOW!

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.

Emerging Trends in Image Processing, Computer Vision and Pattern Recognition

Author : Leonidas Deligiannidis
Publisher : Morgan Kaufmann
ISBN 13 : 012802092X
Total Pages : 640 pages
Book Rating : 4.1/5 (28 download)

DOWNLOAD NOW!

Book Synopsis Emerging Trends in Image Processing, Computer Vision and Pattern Recognition by : Leonidas Deligiannidis

Download or read book Emerging Trends in Image Processing, Computer Vision and Pattern Recognition written by Leonidas Deligiannidis and published by Morgan Kaufmann. This book was released on 2014-12-09 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition discusses the latest in trends in imaging science which at its core consists of three intertwined computer science fields, namely: Image Processing, Computer Vision, and Pattern Recognition. There is significant renewed interest in each of these three fields fueled by Big Data and Data Analytic initiatives including but not limited to; applications as diverse as computational biology, biometrics, biomedical imaging, robotics, security, and knowledge engineering. These three core topics discussed here provide a solid introduction to image processing along with low-level processing techniques, computer vision fundamentals along with examples of applied applications and pattern recognition algorithms and methodologies that will be of value to the image processing and computer vision research communities. Drawing upon the knowledge of recognized experts with years of practical experience and discussing new and novel applications Editors’ Leonidas Deligiannidis and Hamid Arabnia cover; Many perspectives of image processing spanning from fundamental mathematical theory and sampling, to image representation and reconstruction, filtering in spatial and frequency domain, geometrical transformations, and image restoration and segmentation Key application techniques in computer vision some of which are camera networks and vision, image feature extraction, face and gesture recognition and biometric authentication Pattern recognition algorithms including but not limited to; Supervised and unsupervised classification algorithms, Ensemble learning algorithms, and parsing algorithms. How to use image processing and visualization to analyze big data. Discusses novel applications that can benefit from image processing, computer vision and pattern recognition such as computational biology, biometrics, biomedical imaging, robotics, security, and knowledge engineering. Covers key application techniques in computer vision from fundamentals to mid to high level processing some of which are camera networks and vision, image feature extraction, face and gesture recognition and biometric authentication. Presents a number of pattern recognition algorithms and methodologies including but not limited to; supervised and unsupervised classification algorithms, Ensemble learning algorithms, and parsing algorithms. Explains how to use image processing and visualization to analyze big data.