Rough Fuzzy Pattern Recognition

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Rough-Fuzzy Pattern Recognition

Pradipta Maji,Sankar K. Pal
Rough Fuzzy Pattern Recognition Book PDF

Author : Pradipta Maji,Sankar K. Pal
Publisher : John Wiley & Sons
Page : 312 pages
File Size : 46,6 Mb
Release : 2012-02-14
Category : Technology & Engineering
ISBN : 9781118004401

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Rough-Fuzzy Pattern Recognition by Pradipta Maji,Sankar K. Pal Pdf

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

Sankar K. Pal,James F. Peters
Rough Fuzzy Image Analysis Book PDF

Author : Sankar K. Pal,James F. Peters
Publisher : CRC Press
Page : 259 pages
File Size : 47,7 Mb
Release : 2010-05-04
Category : Computers
ISBN : 9781439803301

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Rough Fuzzy Image Analysis by Sankar K. Pal,James F. Peters Pdf

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

Neuro-Fuzzy Pattern Recognition

Sankar K. Pal,Sushmita Mitra
Neuro Fuzzy Pattern Recognition Book PDF

Author : Sankar K. Pal,Sushmita Mitra
Publisher : Wiley-Interscience
Page : 418 pages
File Size : 51,7 Mb
Release : 1999
Category : Computers
ISBN : UOM:39015054399988

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Neuro-Fuzzy Pattern Recognition by Sankar K. Pal,Sushmita Mitra Pdf

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.

Fuzzy Algorithms: With Applications To Image Processing And Pattern Recognition

Zheru Chi,Hong Yan
Fuzzy Algorithms With Applications To Image Processing And Pattern Recognition Book PDF

Author : Zheru Chi,Hong Yan
Publisher : World Scientific
Page : 239 pages
File Size : 52,9 Mb
Release : 1996-10-04
Category : Computers
ISBN : 9789814498852

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Fuzzy Algorithms: With Applications To Image Processing And Pattern Recognition by Zheru Chi,Hong Yan Pdf

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:

Pattern Recognition And Big Data

Pal Sankar Kumar,Pal Amita
Pattern Recognition And Big Data Book PDF

Author : Pal Sankar Kumar,Pal Amita
Publisher : World Scientific
Page : 876 pages
File Size : 45,9 Mb
Release : 2016-12-15
Category : Computers
ISBN : 9789813144569

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Pattern Recognition And Big Data by Pal Sankar Kumar,Pal Amita Pdf

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.

Soft Computing Approach to Pattern Recognition and Image Processing

Ashish Ghosh,Sankar K. Pal
Soft Computing Approach to Pattern Recognition and Image Processing Book PDF

Author : Ashish Ghosh,Sankar K. Pal
Publisher : World Scientific
Page : 374 pages
File Size : 48,8 Mb
Release : 2002
Category : Computers
ISBN : 9812776230

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Soft Computing Approach to Pattern Recognition and Image Processing by Ashish Ghosh,Sankar K. Pal Pdf

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.

Granular Neural Networks, Pattern Recognition and Bioinformatics

Sankar K. Pal,Shubhra S. Ray,Avatharam Ganivada
Granular Neural Networks Pattern Recognition and Bioinformatics Book PDF

Author : Sankar K. Pal,Shubhra S. Ray,Avatharam Ganivada
Publisher : Springer
Page : 227 pages
File Size : 55,6 Mb
Release : 2017-05-02
Category : Technology & Engineering
ISBN : 9783319571157

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Granular Neural Networks, Pattern Recognition and Bioinformatics by Sankar K. Pal,Shubhra S. Ray,Avatharam Ganivada Pdf

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.

Neuro-Fuzzy Pattern Recognition

H Bunke,A Kandel
Neuro Fuzzy Pattern Recognition Book PDF

Author : H Bunke,A Kandel
Publisher : World Scientific
Page : 276 pages
File Size : 44,8 Mb
Release : 2000-12-22
Category : Computers
ISBN : 9789814492393

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Neuro-Fuzzy Pattern Recognition by H Bunke,A Kandel Pdf

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. Contents: Methodology:Simultaneous Feature Analysis and System Identification in a Neuro-Fuzzy Framework (N R Pal & D Chakraborty)Neuro-Fuzzy Model for Unsupervised Feature Extraction with Real Life Applications (R K De et al.)A Computational-Intelligence-Based Approach to Decision Support (M B Gorzalczany)Clustering Problem Using Fuzzy C-Means Algorithms and Unsupervised Neural Networks (J-S Lin)Automatic Training of Min-Max Classifiers (A Rizzi)Granular Computing in Pattern Recognition (W Pedrycz & G Vukovich)ART-Based Model Set for Pattern Recognition: FasArt Family (G I Sainz Palmero et al.)Applications:A Methodology and a System for Adaptive Speech Recognition in a Noisy Environment Based on Adaptive Noise Cancellation and Evolving Fuzzy Neural Networks (N Kasabov & G Iliev)Neural Versus Heuristic Development of Choquet Fuzzy Integral Fusion Algorithms for Land Mine Detection (P D Gader et al.)Automatic Segmentation of Multi-Spectral MR Brain Images Using a Neuro-Fuzzy Algorithm (S Y Lee et al.)Vision-Based Neuro-Fuzzy Control of Autonomous Lane Following Vehicle (Y-J Ryoo) Readership: Graduate students, lecturers and researchers in computer science and computer engineering. Keywords:Neuro-Fuzzy;Fuzzy Logic;Neural Networks;Pattern Recognition;Classification;Clustering;Decision Making;Uncertainty Management

Scalable Pattern Recognition Algorithms

Pradipta Maji,Sushmita Paul
Scalable Pattern Recognition Algorithms Book PDF

Author : Pradipta Maji,Sushmita Paul
Publisher : Springer Science & Business Media
Page : 316 pages
File Size : 46,8 Mb
Release : 2014-03-19
Category : Computers
ISBN : 9783319056302

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Scalable Pattern Recognition Algorithms by Pradipta Maji,Sushmita Paul Pdf

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.

Pattern Recognition with Fuzzy Objective Function Algorithms

James C. Bezdek
Pattern Recognition with Fuzzy Objective Function Algorithms Book PDF

Author : James C. Bezdek
Publisher : Springer Science & Business Media
Page : 267 pages
File Size : 53,7 Mb
Release : 2013-03-13
Category : Mathematics
ISBN : 9781475704501

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Pattern Recognition with Fuzzy Objective Function Algorithms by James C. Bezdek Pdf

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.

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

Guoyin Wang
Rough Sets Fuzzy Sets Data Mining and Granular Computing Book PDF

Author : Guoyin Wang
Publisher : Springer Science & Business Media
Page : 758 pages
File Size : 53,9 Mb
Release : 2003-05-08
Category : Computers
ISBN : 9783540140405

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing by Guoyin Wang Pdf

This book constitutes the refereed proceedings of the 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, RSFDGrC 2003, held in Chongqing, China in May 2003. The 39 revised full papers and 75 revised short papers presented together with 2 invited keynote papers and 11 invited plenary papers were carefully reviewed and selected from a total of 245 submissions. The papers are organized in topical sections on rough sets foundations and methods; fuzzy sets and systems; granular computing; neural networks and evolutionary computing; data mining, machine learning, and pattern recognition; logics and reasoning; multi-agent systems; and Web intelligence and intelligent systems.

Neuro-fuzzy Pattern Recognition

Horst Bunke,Abraham Kandel
Neuro fuzzy Pattern Recognition Book PDF

Author : Horst Bunke,Abraham Kandel
Publisher : World Scientific
Page : 276 pages
File Size : 53,5 Mb
Release : 2000
Category : Computers
ISBN : 9789810244187

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Neuro-fuzzy Pattern Recognition by Horst Bunke,Abraham Kandel Pdf

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

Pramod Kumar Pisharady,Prahlad Vadakkepat,Loh Ai Poh
Computational Intelligence in Multi Feature Visual Pattern Recognition Book PDF

Author : Pramod Kumar Pisharady,Prahlad Vadakkepat,Loh Ai Poh
Publisher : Springer
Page : 142 pages
File Size : 52,5 Mb
Release : 2014-05-23
Category : Technology & Engineering
ISBN : 9789812870568

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Computational Intelligence in Multi-Feature Visual Pattern Recognition by Pramod Kumar Pisharady,Prahlad Vadakkepat,Loh Ai Poh Pdf

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.

Pattern Recognition and Machine Intelligence

Marzena Kryszkiewicz,Sanghamitra Bandyopadhyay,Henryk Rybinski,Sankar K. Pal
Pattern Recognition and Machine Intelligence Book PDF

Author : Marzena Kryszkiewicz,Sanghamitra Bandyopadhyay,Henryk Rybinski,Sankar K. Pal
Publisher : Springer
Page : 588 pages
File Size : 46,5 Mb
Release : 2015-06-22
Category : Computers
ISBN : 9783319199412

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Pattern Recognition and Machine Intelligence by Marzena Kryszkiewicz,Sanghamitra Bandyopadhyay,Henryk Rybinski,Sankar K. Pal Pdf

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

Davide Ciucci,Masahiro Inuiguchi,Yiyu Yao,Dominik Slezak,Guoyin Wang
Rough Sets Fuzzy Sets Data Mining and Granular Computing Book PDF

Author : Davide Ciucci,Masahiro Inuiguchi,Yiyu Yao,Dominik Slezak,Guoyin Wang
Publisher : Springer
Page : 412 pages
File Size : 53,8 Mb
Release : 2013-10-07
Category : Computers
ISBN : 9783642412189

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing by Davide Ciucci,Masahiro Inuiguchi,Yiyu Yao,Dominik Slezak,Guoyin Wang Pdf

This book constitutes the thoroughly refereed conference proceedings of the 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2013, held in Halifax, Canada in October 2013 as one of the co-located conference of the 2013 Joint Rough Set Symposium, JRS 2013. The 69 papers (including 44 regular and 25 short papers) included in the JRS proceedings (LNCS 8170 and LNCS 8171) were carefully reviewed and selected from 106 submissions. The papers in this volume cover topics such as inconsistency, incompleteness, non-determinism; fuzzy and rough hybridization; granular computing and covering-based rough sets; soft clustering; image and medical data analysis.