Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Genetic Algorithms For Pattern Recognition
Download Genetic Algorithms For Pattern Recognition full books in PDF, epub, and Kindle. Read online Genetic Algorithms For Pattern Recognition ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Genetic Algorithms for Pattern Recognition by : Sankar K. Pal
Download or read book Genetic Algorithms for Pattern Recognition written by Sankar K. Pal and published by CRC Press. This book was released on 2017-11-22 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving pattern recognition problems involves an enormous amount of computational effort. By applying genetic algorithms - a computational method based on the way chromosomes in DNA recombine - these problems are more efficiently and more accurately solved. Genetic Algorithms for Pattern Recognition covers a broad range of applications in science and technology, describing the integration of genetic algorithms in pattern recognition and machine learning problems to build intelligent recognition systems. The articles, written by leading experts from around the world, accomplish several objectives: they provide insight into the theory of genetic algorithms; they develop pattern recognition theory in light of genetic algorithms; and they illustrate applications in artificial neural networks and fuzzy logic. The cross-sectional view of current research presented in Genetic Algorithms for Pattern Recognition makes it a unique text, ideal for graduate students and researchers.
Author :Sanghamitra Bandyopadhyay Publisher :Springer Science & Business Media ISBN 13 :3540496076 Total Pages :320 pages Book Rating :4.5/5 (44 download)
Book Synopsis Classification and Learning Using Genetic Algorithms by : Sanghamitra Bandyopadhyay
Download or read book Classification and Learning Using Genetic Algorithms written by Sanghamitra Bandyopadhyay and published by Springer Science & Business Media. This book was released on 2007-05-17 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries. Coverage also demonstrates the effectiveness of the genetic classifiers vis-à-vis several widely used classifiers, including neural networks.
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.
Book Synopsis Pattern Recognition by : Sankar K. Pal
Download or read book Pattern Recognition written by Sankar K. Pal and published by World Scientific. This book was released on 2001 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, containing contributions by experts from all over the world, is a collection of 21 articles which present review and research material describing the evolution and recent developments of various pattern recognition methodologies, ranging from statistical, syntactic/linguistic, fuzzy-set-theoretic, neural, genetic-algorithmic and rough-set-theoretic to hybrid soft computing, with significant real-life applications. In addition, the book describes efficient soft machine learning algorithms for data mining and knowledge discovery. With a balanced mixture of theory, algorithms and applications, as well as up-to-date information and an extensive bibliography, Pattern Recognition: From Classical to Modern Approaches is a very useful resource. Contents: Pattern Recognition: Evolution of Methodologies and Data Mining (A Pal & S K Pal); Adaptive Stochastic Algorithms for Pattern Classification (M A L Thathachar & P S Sastry); Shape in Images (K V Mardia); Decision Trees for Classification: A Review and Some New Results (R Kothari & M Dong); Syntactic Pattern Recognition (A K Majumder & A K Ray); Fuzzy Sets as a Logic Canvas for Pattern Recognition (W Pedrycz & N Pizzi); Neural Network Based Pattern Recognition (V David Sanchez A); Networks of Spiking Neurons in Data Mining (K Cios & D M Sala); Genetic Algorithms, Pattern Classification and Neural Networks Design (S Bandyopadhyay et al.); Rough Sets in Pattern Recognition (A Skowron & R Swiniarski); Automated Generation of Qualitative Representations of Complex Objects by Hybrid Soft-Computing Methods (E H Ruspini & I S Zwir); Writing Speed and Writing Sequence Invariant On-line Handwriting Recognition (S-H Cha & S N Srihari); Tongue Diagnosis Based on Biometric Pattern Recognition Technology (K Wang et al.); and other papers. Readership: Graduate students, researchers and academics in pattern recognition.
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.
Book Synopsis Genetic Algorithms and their Applications by : John J. Grefenstette
Download or read book Genetic Algorithms and their Applications written by John J. Grefenstette and published by Psychology Press. This book was released on 2013-08-21 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: First Published in 1987. This is the collected proceedings of the second International Conference on Genetic Algorithms held at the Massachusetts Institute of Technology, Cambridge, MA on the 28th to the 31st July 1987. With papers on Genetic search theory, Adaptive search operators, representation issues, connectionism and parallelism, credit assignment ad learning, and applications.
Book Synopsis Evolutionary Synthesis of Pattern Recognition Systems by : Bir Bhanu
Download or read book Evolutionary Synthesis of Pattern Recognition Systems written by Bir Bhanu and published by Springer Science & Business Media. This book was released on 2006-03-30 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrates computer vision, pattern recognition, and AI. Presents original research that will benefit researchers and professionals in computer vision, pattern recognition, target recognition, machine learning, evolutionary learning, image processing, knowledge discovery and data mining, cybernetics, robotics, automation and psychology
Book Synopsis Pattern Recognition Analysis Via Genetic Algorithms and Multivariate Statistical Methods by : Barry K. Levine
Download or read book Pattern Recognition Analysis Via Genetic Algorithms and Multivariate Statistical Methods written by Barry K. Levine and published by . This book was released on 1999-02 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is written for researchers interested in categorizing samples on the basis of regularities in observed data. This text is more than just an introduction to the application of pattern recognition methods to problems in chemistry and chemical engineering. It is intended to serve as a primary source of information for pattern recognition techniques that are useful for the analysis of experimental data. The concepts are presented in an easily understood manner for use by readers with only a basic knowledge of statistics.
Book Synopsis Genetic Algorithms for Pattern Recognition by : Sankar K. Pal
Download or read book Genetic Algorithms for Pattern Recognition written by Sankar K. Pal and published by CRC Press. This book was released on 2017-11-22 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving pattern recognition problems involves an enormous amount of computational effort. By applying genetic algorithms - a computational method based on the way chromosomes in DNA recombine - these problems are more efficiently and more accurately solved. Genetic Algorithms for Pattern Recognition covers a broad range of applications in science and technology, describing the integration of genetic algorithms in pattern recognition and machine learning problems to build intelligent recognition systems. The articles, written by leading experts from around the world, accomplish several objectives: they provide insight into the theory of genetic algorithms; they develop pattern recognition theory in light of genetic algorithms; and they illustrate applications in artificial neural networks and fuzzy logic. The cross-sectional view of current research presented in Genetic Algorithms for Pattern Recognition makes it a unique text, ideal for graduate students and researchers.
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 304 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.
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.
Book Synopsis Feature Extraction, Construction and Selection by : Huan Liu
Download or read book Feature Extraction, Construction and Selection written by Huan Liu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is broad interest in feature extraction, construction, and selection among practitioners from statistics, pattern recognition, and data mining to machine learning. Data preprocessing is an essential step in the knowledge discovery process for real-world applications. This book compiles contributions from many leading and active researchers in this growing field and paints a picture of the state-of-art techniques that can boost the capabilities of many existing data mining tools. The objective of this collection is to increase the awareness of the data mining community about the research of feature extraction, construction and selection, which are currently conducted mainly in isolation. This book is part of our endeavor to produce a contemporary overview of modern solutions, to create synergy among these seemingly different branches, and to pave the way for developing meta-systems and novel approaches. Even with today's advanced computer technologies, discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Feature extraction, construction and selection are a set of techniques that transform and simplify data so as to make data mining tasks easier. Feature construction and selection can be viewed as two sides of the representation problem.
Book Synopsis Soft Computing Approach to Pattern Recognition and Image Processing by :
Download or read book Soft Computing Approach to Pattern Recognition and Image Processing written by and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Pattern Mining with Evolutionary Algorithms by : Sebastián Ventura
Download or read book Pattern Mining with Evolutionary Algorithms written by Sebastián Ventura and published by Springer. This book was released on 2016-06-13 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the field of pattern mining with evolutionary algorithms. To do so, it covers formal definitions about patterns, patterns mining, type of patterns and the usefulness of patterns in the knowledge discovery process. As it is described within the book, the discovery process suffers from both high runtime and memory requirements, especially when high dimensional datasets are analyzed. To solve this issue, many pruning strategies have been developed. Nevertheless, with the growing interest in the storage of information, more and more datasets comprise such a dimensionality that the discovery of interesting patterns becomes a challenging process. In this regard, the use of evolutionary algorithms for mining pattern enables the computation capacity to be reduced, providing sufficiently good solutions. This book offers a survey on evolutionary computation with particular emphasis on genetic algorithms and genetic programming. Also included is an analysis of the set of quality measures most widely used in the field of pattern mining with evolutionary algorithms. This book serves as a review of the most important evolutionary algorithms for pattern mining. It considers the analysis of different algorithms for mining different type of patterns and relationships between patterns, such as frequent patterns, infrequent patterns, patterns defined in a continuous domain, or even positive and negative patterns. A completely new problem in the pattern mining field, mining of exceptional relationships between patterns, is discussed. In this problem the goal is to identify patterns which distribution is exceptionally different from the distribution in the complete set of data records. Finally, the book deals with the subgroup discovery task, a method to identify a subgroup of interesting patterns that is related to a dependent variable or target attribute. This subgroup of patterns satisfies two essential conditions: interpretability and interestingness.
Author :José Francisco Martinez-Trinidad Publisher :Springer Science & Business Media ISBN 13 :3642215866 Total Pages :364 pages Book Rating :4.6/5 (422 download)
Book Synopsis Pattern Recognition by : José Francisco Martinez-Trinidad
Download or read book Pattern Recognition written by José Francisco Martinez-Trinidad and published by Springer Science & Business Media. This book was released on 2011-06-16 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third Mexican Conference on Pattern Recognition, MCPR 2011, held in Cancun, Mexico, in June/July 2011. The 37 revised full papers were carefully reviewed and selected from 69 submissions and are organized in topical sections on pattern recognition and data mining; computer vision and robotics; image processing; neural networks and signal processing; and natural language and document processing.
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 Science & Business Media. This book was released on 2001-02-28 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Conference on Advances in Pattern Recognition, ICAPR 2001, held in Rio de Janeiro, Brazil in March 2001. The 40 revised full papers presented together with three invited papers and two tutorial presentations were carefully reviewed and selected for inclusion in the proceedings. The book is organized in topical sections on neural networks and computational intelligence, character recognition and document analysis, feature selection and analysis, pattern recognition and classification, image and signal processing applications, and image feature analysis and retrieval.
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.
