Hybrid one‑class classifier ensemble based on fuzzy integral for open‑lexicon handwritten Arabic word recognition

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Publisher : Infinite Study
ISBN 13 :
Total Pages : 15 pages
Book Rating : 4./5 ( download)

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Book Synopsis Hybrid one‑class classifier ensemble based on fuzzy integral for open‑lexicon handwritten Arabic word recognition by : Bilal Hadjadji

Download or read book Hybrid one‑class classifier ensemble based on fuzzy integral for open‑lexicon handwritten Arabic word recognition written by Bilal Hadjadji and published by Infinite Study. This book was released on with total page 15 pages. Available in PDF, EPUB and Kindle. Book excerpt: One-class classifier (OCC) is involved for solving different kinds of problems due to its ability to represent a class distribution regardless the remaining classes. Its main advantage for multi-class classification is offering an open system and therefore allows easily extending new classes without retraining OCCs. So far, hidden Markov models, support vector machines and neural networks are the most used classifiers for Arabic word recognition, which provides a system with closed lexicon. In this paper, the OCCs are explored in order to perform an Arabic word recognition system with an open lexicon. Generally, pattern recognition systems designed by a single system suffer from limitations such as the lack of uniqueness and non-universality. Thus, combining multiple systems becomes an attractive research topic for performance and robustness enhancement. Fixed rules are commonly used us combiners for the hybrid OCC ensembles. The present paper aims to propose a combination scheme of OCCs based on the use of fuzzy integral (FI) operators. Furthermore, an alternative framework is proposed to design a parameter-independent and open-lexicon handwritten Arabic word recognition system as well as a new density measure function. Experimental results conducted on Arabic handwritten dataset using different types of OCCs with large number of classes highlight the superiority of FI for hybrid OCC ensembles.

Markov Models for Handwriting Recognition

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Publisher : Springer Science & Business Media
ISBN 13 : 9781447121886
Total Pages : 78 pages
Book Rating : 4.1/5 (218 download)

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Book Synopsis Markov Models for Handwriting Recognition by : Thomas Plötz

Download or read book Markov Models for Handwriting Recognition written by Thomas Plötz and published by Springer Science & Business Media. This book was released on 2012-02-02 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden Markov models and Markov-chain or n-gram models. First, the text introduces the typical architecture of a Markov model-based handwriting recognition system, and familiarizes the reader with the essential theoretical concepts behind Markovian models. Then, the text reviews proposed solutions in the literature for open problems in applying Markov model-based approaches to automatic handwriting recognition.

Recent Advances in Natural Language Processing

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Publisher : John Benjamins Publishing
ISBN 13 : 9027236402
Total Pages : 487 pages
Book Rating : 4.0/5 (272 download)

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Book Synopsis Recent Advances in Natural Language Processing by : Ruslan Mitkov

Download or read book Recent Advances in Natural Language Processing written by Ruslan Mitkov and published by John Benjamins Publishing. This book was released on 1997-01-01 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is based on contributions from the First International Conference on “Recent Advances in Natural Language Processing” (RANLP'95) held in Tzigov Chark, Bulgaria, 14-16 September 1995. This conference was one of the most important and competitively reviewed conferences in Natural Language Processing (NLP) for 1995 with submissions from more than 30 countries. Of the 48 papers presented at RANLP'95, the best (revised) papers have been selected for this book, in the hope that they reflect the most significant and promising trends (and latest successful results) in NLP. The book is organised thematically and the contributions are grouped according to the traditional topics found in NLP: morphology, syntax, grammars, parsing, semantics, discourse, grammars, generation, machine translation, corpus processing and multimedia. To help the reader find his/her way, the authors have prepared an extensive index which contains major terms used in NLP; an index of authors which lists the names of the authors and the page numbers of their paper(s); a list of figures; and a list of tables. This book will be of interest to researchers, lecturers and graduate students interested in Natural Language Processing and more specifically to those who work in Computational Linguistics, Corpus Linguistics and Machine Translation.

Character Recognition Systems

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Publisher : John Wiley & Sons
ISBN 13 : 9780470176528
Total Pages : 351 pages
Book Rating : 4.1/5 (765 download)

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Book Synopsis Character Recognition Systems by : Mohamed Cheriet

Download or read book Character Recognition Systems written by Mohamed Cheriet and published by John Wiley & Sons. This book was released on 2007-11-27 with total page 351 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Much of pattern recognition theory and practice, including methods such as Support Vector Machines, has emerged in an attempt to solve the character recognition problem. This book is written by very well-known academics who have worked in the field for many years and have made significant and lasting contributions. The book will no doubt be of value to students and practitioners." -Sargur N. Srihari, SUNY Distinguished Professor, Department of Computer Science and Engineering, and Director, Center of Excellence for Document Analysis and Recognition (CEDAR), University at Buffalo, The State University of New York "The disciplines of optical character recognition and document image analysis have a history of more than forty years. In the last decade, the importance and popularity of these areas have grown enormously. Surprisingly, however, the field is not well covered by any textbook. This book has been written by prominent leaders in the field. It includes all important topics in optical character recognition and document analysis, and is written in a very coherent and comprehensive style. This book satisfies an urgent need. It is a volume the community has been awaiting for a long time, and I can enthusiastically recommend it to everybody working in the area." -Horst Bunke, Professor, Institute of Computer Science and Applied Mathematics (IAM), University of Bern, Switzerland In Character Recognition Systems, the authors provide practitioners and students with the fundamental principles and state-of-the-art computational methods of reading printed texts and handwritten materials. The information presented is analogous to the stages of a computer recognition system, helping readers master the theory and latest methodologies used in character recognition in a meaningful way. This book covers: * Perspectives on the history, applications, and evolution of Optical Character Recognition (OCR) * The most widely used pre-processing techniques, as well as methods for extracting character contours and skeletons * Evaluating extracted features, both structural and statistical * Modern classification methods that are successful in character recognition, including statistical methods, Artificial Neural Networks (ANN), Support Vector Machines (SVM), structural methods, and multi-classifier methods * An overview of word and string recognition methods and techniques * Case studies that illustrate practical applications, with descriptions of the methods and theories behind the experimental results Each chapter contains major steps and tricks to handle the tasks described at-hand. Researchers and graduate students in computer science and engineering will find this book useful for designing a concrete system in OCR technology, while practitioners will rely on it as a valuable resource for the latest advances and modern technologies that aren't covered elsewhere in a single book.

Optical Character Recognition Systems for Different Languages with Soft Computing

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Publisher : Springer
ISBN 13 : 3319502522
Total Pages : 248 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Optical Character Recognition Systems for Different Languages with Soft Computing by : Arindam Chaudhuri

Download or read book Optical Character Recognition Systems for Different Languages with Soft Computing written by Arindam Chaudhuri and published by Springer. This book was released on 2016-12-23 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.

Supervised Sequence Labelling with Recurrent Neural Networks

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Publisher : Springer
ISBN 13 : 3642247970
Total Pages : 146 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Supervised Sequence Labelling with Recurrent Neural Networks by : Alex Graves

Download or read book Supervised Sequence Labelling with Recurrent Neural Networks written by Alex Graves and published by Springer. This book was released on 2012-02-06 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supervised sequence labelling is a vital area of machine learning, encompassing tasks such as speech, handwriting and gesture recognition, protein secondary structure prediction and part-of-speech tagging. Recurrent neural networks are powerful sequence learning tools—robust to input noise and distortion, able to exploit long-range contextual information—that would seem ideally suited to such problems. However their role in large-scale sequence labelling systems has so far been auxiliary. The goal of this book is a complete framework for classifying and transcribing sequential data with recurrent neural networks only. Three main innovations are introduced in order to realise this goal. Firstly, the connectionist temporal classification output layer allows the framework to be trained with unsegmented target sequences, such as phoneme-level speech transcriptions; this is in contrast to previous connectionist approaches, which were dependent on error-prone prior segmentation. Secondly, multidimensional recurrent neural networks extend the framework in a natural way to data with more than one spatio-temporal dimension, such as images and videos. Thirdly, the use of hierarchical subsampling makes it feasible to apply the framework to very large or high resolution sequences, such as raw audio or video. Experimental validation is provided by state-of-the-art results in speech and handwriting recognition.

Deep Learning with Python

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Publisher : Simon and Schuster
ISBN 13 : 1638352046
Total Pages : 597 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning with Python by : Francois Chollet

Download or read book Deep Learning with Python written by Francois Chollet and published by Simon and Schuster. This book was released on 2017-11-30 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

Introduction to Information Retrieval

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Publisher : Cambridge University Press
ISBN 13 : 1139472100
Total Pages : pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Introduction to Information Retrieval by : Christopher D. Manning

Download or read book Introduction to Information Retrieval written by Christopher D. Manning and published by Cambridge University Press. This book was released on 2008-07-07 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.

Proceedings of International Conference on Frontiers in Computing and Systems

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Publisher : Springer Nature
ISBN 13 : 9811578346
Total Pages : 895 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Proceedings of International Conference on Frontiers in Computing and Systems by : Debotosh Bhattacharjee

Download or read book Proceedings of International Conference on Frontiers in Computing and Systems written by Debotosh Bhattacharjee and published by Springer Nature. This book was released on 2020-11-23 with total page 895 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers outstanding research papers presented at the International Conference on Frontiers in Computing and Systems (COMSYS 2020), held on January 13–15, 2019 at Jalpaiguri Government Engineering College, West Bengal, India and jointly organized by the Department of Computer Science & Engineering and Department of Electronics & Communication Engineering. The book presents the latest research and results in various fields of machine learning, computational intelligence, VLSI, networks and systems, computational biology, and security, making it a rich source of reference material for academia and industry alike.

Genre in a Changing World

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Publisher : Parlor Press LLC
ISBN 13 : 1643170015
Total Pages : 486 pages
Book Rating : 4.6/5 (431 download)

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Book Synopsis Genre in a Changing World by : Charles Bazerman

Download or read book Genre in a Changing World written by Charles Bazerman and published by Parlor Press LLC. This book was released on 2009-09-16 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Genre studies and genre approaches to literacy instruction continue to develop in many regions and from a widening variety of approaches. Genre has provided a key to understanding the varying literacy cultures of regions, disciplines, professions, and educational settings. GENRE IN A CHANGING WORLD provides a wide-ranging sampler of the remarkable variety of current work. The twenty-four chapters in this volume, reflecting the work of scholars in Europe, Australasia, and North and South America, were selected from the over 400 presentations at SIGET IV (the Fourth International Symposium on Genre Studies) held on the campus of UNISUL in Tubarão, Santa Catarina, Brazil in August 2007—the largest gathering on genre to that date. The chapters also represent a wide variety of approaches, including rhetoric, Systemic Functional Linguistics, media and critical cultural studies, sociology, phenomenology, enunciation theory, the Geneva school of educational sequences, cognitive psychology, relevance theory, sociocultural psychology, activity theory, Gestalt psychology, and schema theory. Sections are devoted to theoretical issues, studies of genres in the professions, studies of genre and media, teaching and learning genre, and writing across the curriculum. The broad selection of material in this volume displays the full range of contemporary genre studies and sets the ground for a next generation of work.

Distinction

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Publisher : Routledge
ISBN 13 : 113587316X
Total Pages : 641 pages
Book Rating : 4.1/5 (358 download)

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Book Synopsis Distinction by : Pierre Bourdieu

Download or read book Distinction written by Pierre Bourdieu and published by Routledge. This book was released on 2013-04-15 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examines differences in taste between modern French classes, discusses the relationship between culture and politics, and outlines the strategies of pretension.

Advances in Signal Processing and Intelligent Recognition Systems

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Publisher : Springer Nature
ISBN 13 : 9811548285
Total Pages : 414 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Advances in Signal Processing and Intelligent Recognition Systems by : Sabu M. Thampi

Download or read book Advances in Signal Processing and Intelligent Recognition Systems written by Sabu M. Thampi and published by Springer Nature. This book was released on 2020-04-30 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Symposium on Advances in Signal Processing and Intelligent Recognition Systems, SIRS 2019, held in Trivandrum, India, in December 2019. The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 63 submissions. The papers cover wide research fields including information retrieval, human-computer interaction (HCI), information extraction, speech recognition.

Deep Learning

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Publisher : MIT Press
ISBN 13 : 0262337371
Total Pages : 801 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Deep Learning by : Ian Goodfellow

Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

Software Studies

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Publisher : MIT Press
ISBN 13 : 0262062747
Total Pages : 349 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Software Studies by : Matthew Fuller

Download or read book Software Studies written by Matthew Fuller and published by MIT Press. This book was released on 2008 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of short expository, critical and speculative texts offers a field guide to the cultural, political, social and aesthetic impact of software. Experts from a range of disciplines each take a key topic in software and the understanding of software, such as algorithms and logical structures.

Big Data, Cloud and Applications

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Publisher : Springer
ISBN 13 : 3319962922
Total Pages : 560 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Big Data, Cloud and Applications by : Youness Tabii

Download or read book Big Data, Cloud and Applications written by Youness Tabii and published by Springer. This book was released on 2018-08-13 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the Third International Conference on Big Data, Cloud and Applications, BDCA 2018, held in Kenitra, Morocco, in April 2018.The 45 revised full papers presented in this book were carefully selected from 99 submissions with a thorough double-blind review process. They focus on the following topics: big data, cloud computing, machine learning, deep learning, data analysis, neural networks, information system and social media, image processing and applications, and natural language processing.

Measuring Research

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Publisher : Oxford University Press
ISBN 13 : 0190640111
Total Pages : 169 pages
Book Rating : 4.1/5 (96 download)

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Book Synopsis Measuring Research by : Cassidy R. Sugimoto

Download or read book Measuring Research written by Cassidy R. Sugimoto and published by Oxford University Press. This book was released on 2018 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: Policy makers, academic administrators, scholars, and members of the public are clamoring for indicators of the value and reach of research. The question of how to quantify the impact and importance of research and scholarly output, from the publication of books and journal articles to the indexing of citations and tweets, is a critical one in predicting innovation, and in deciding what sorts of research is supported and whom is hired to carry it out. There is a wide set of data and tools available for measuring research, but they are often used in crude ways, and each have their own limitations and internal logics. Measuring Research: What Everyone Needs to Know(R) will provide, for the first time, an accessible account of the methods used to gather and analyze data on research output and impact. Following a brief history of scholarly communication and its measurement -- from traditional peer review to crowdsourced review on the social web -- the book will look at the classification of knowledge and academic disciplines, the differences between citations and references, the role of peer review, national research evaluation exercises, the tools used to measure research, the many different types of measurement indicators, and how to measure interdisciplinarity. The book also addresses emerging issues within scholarly communication, including whether or not measurement promotes a "publish or perish" culture, fraud in research, or "citation cartels." It will also look at the stakeholders behind these analytical tools, the adverse effects of these quantifications, and the future of research measurement.

Markov Models for Pattern Recognition

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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.