Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Download or read book Pattern Recognition and Machine Intelligence written by B. Uma Shankar and published by Springer. This book was released on 2017-11-22 with total page 705 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2017,held in Kolkata, India, in December 2017. The total of 86 full papers presented in this volume were carefully reviewed and selected from 293 submissions. They were organized in topical sections named: pattern recognition and machine learning; signal and image processing; computer vision and video processing; soft and natural computing; speech and natural language processing; bioinformatics and computational biology; data mining and big data analytics; deep learning; spatial data science and engineering; and applications of pattern recognition and machine intelligence.

Download or read book Pattern Recognition Machine Intelligence and Biometrics written by Patrick S. P. Wang and published by Springer Science & Business Media. This book was released on 2012-02-13 with total page 883 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Pattern Recognition, Machine Intelligence and Biometrics" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland security. In addition, computer modeling and simulations of human behaviors are addressed in this collection of 31 chapters by top-ranked professionals from all over the world in the field of PR/AI/Biometrics. The book is intended for researchers and graduate students in Computer and Information Science, and in Communication and Control Engineering. Dr. Patrick S. P. Wang is a Professor Emeritus at the College of Computer and Information Science, Northeastern University, USA, Zijiang Chair of ECNU, Shanghai, and NSC Visiting Chair Professor of NTUST, Taipei.

Download or read book Pattern Recognition and Machine Intelligence written by Pradipta Maji and published by Springer. This book was released on 2013-12-09 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2013, held in Kolkata, India in December 2013. The 101 revised papers presented together with 9 invited talks were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on pattern recognition; machine learning; image processing; speech and video processing; medical imaging; document image processing; soft computing; bioinformatics and computational biology; and social media mining.

Download or read book Pattern Recognition and Machine Learning written by Y. Anzai and published by Elsevier. This book was released on 2012-12-02 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

Download or read book Pattern Recognition and Machine Learning written by King-Sun Fu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the Proceedings of the US-Japan Seminar on Learning Process in Control Systems. The seminar, held in Nagoya, Japan, from August 18 to 20, 1970, was sponsored by the US-Japan Cooperative Science Program, jointly supported by the National Science Foundation and the Japan Society for the Promotion of Science. The full texts of all the presented papers except two t are included. The papers cover a great variety of topics related to learning processes and systems, ranging from pattern recognition to systems identification, from learning control to biological modelling. In order to reflect the actual content of the book, the present title was selected. All the twenty-eight papers are roughly divided into two parts--Pattern Recognition and System Identification and Learning Process and Learning Control. It is sometimes quite obvious that some papers can be classified into either part. The choice in these cases was strictly the editor's in order to keep a certain balance between the two parts. During the past decade there has been a considerable growth of interest in problems of pattern recognition and machine learn ing. In designing an optimal pattern recognition or control system, if all the a priori information about the process under study is known and can be described deterministically, the optimal system is usually designed by deterministic optimization techniques.

Download or read book The Pattern Recognition Basis of Artificial Intelligence written by Donald Tveter and published by Wiley-IEEE Computer Society Press. This book was released on 1998 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book pays extra attention to the new ideas in AI: neural networking, case based reasoning, and memory based reasoning, while including the important aspects of traditional symbol processing AI. As much as possible, these methods are compared with each other so that the reader will see the advantages and disadvantages of each method. Second, the new and traditional methods are presented as different ways of doing pattern recognition, giving unity to the subject matter. Third, rather than treating AI as just a collection of advanced algorithms, it also looks at the problems involved in producing the kind of general purpose intelligence found in human beings who have to deal with the real world.

Download or read book Advances In Pattern Recognition And Artificial Intelligence written by Marleah Blom and published by World Scientific. This book was released on 2021-11-16 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes reviewed papers by international scholars from the 2020 International Conference on Pattern Recognition and Artificial Intelligence (held online). The papers have been expanded to provide more details specifically for the book. It is geared to promote ongoing interest and understanding about pattern recognition and artificial intelligence. Like the previous book in the series, this book covers a range of topics and illustrates potential areas where pattern recognition and artificial intelligence can be applied. It highlights, for example, how pattern recognition and artificial intelligence can be used to classify, predict, detect and help promote further discoveries related to credit scores, criminal news, national elections, license plates, gender, personality characteristics, health, and more.Chapters include works centred on medical and financial applications as well as topics related to handwriting analysis and text processing, internet security, image analysis, database creation, neural networks and deep learning. While the book is geared to promote interest from the general public, it may also be of interest to graduate students and researchers in the field.

Download or read book Progress in Artificial Intelligence and Pattern Recognition written by Yanio Hernández Heredia and published by Springer. This book was released on 2021-11-04 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Workshop on Artificial Intelligence and Pattern Recognition, IWAIPR 2021, held in Havana, Cuba, in October 2021. The 42 full papers presented were carefully reviewed and selected from 73 submissions. The papers promote and disseminate ongoing research on mathematical methods and computing techniques for artificial intelligence and pattern recognition, in particular in bioinformatics, cognitive and humanoid vision, computer vision, image analysis and intelligent data analysis.

Download or read book Artificial Neural Networks and Statistical Pattern Recognition written by I.K. Sethi and published by Elsevier. This book was released on 2014-06-28 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the growing complexity of pattern recognition related problems being solved using Artificial Neural Networks, many ANN researchers are grappling with design issues such as the size of the network, the number of training patterns, and performance assessment and bounds. These researchers are continually rediscovering that many learning procedures lack the scaling property; the procedures simply fail, or yield unsatisfactory results when applied to problems of bigger size. Phenomena like these are very familiar to researchers in statistical pattern recognition (SPR), where the curse of dimensionality is a well-known dilemma. Issues related to the training and test sample sizes, feature space dimensionality, and the discriminatory power of different classifier types have all been extensively studied in the SPR literature. It appears however that many ANN researchers looking at pattern recognition problems are not aware of the ties between their field and SPR, and are therefore unable to successfully exploit work that has already been done in SPR. Similarly, many pattern recognition and computer vision researchers do not realize the potential of the ANN approach to solve problems such as feature extraction, segmentation, and object recognition. The present volume is designed as a contribution to the greater interaction between the ANN and SPR research communities.

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 596 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.

Download or read book Pattern Recognition and Computational Intelligence Techniques Using Matlab written by E. S. Gopi and published by Springer Nature. This book was released on 2019-10-17 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the complex topic of using computational intelligence for pattern recognition in a straightforward and applicable way, using Matlab to illustrate topics and concepts. The author covers computational intelligence tools like particle swarm optimization, bacterial foraging, simulated annealing, genetic algorithm, and artificial neural networks. The Matlab based illustrations along with the code are given for every topic. Readers get a quick basic understanding of various pattern recognition techniques using only the required depth in math. The Matlab program and algorithm are given along with the running text, providing clarity and usefulness of the various techniques. Presents pattern recognition and the computational intelligence using Matlab; Includes mixtures of theory, math, and algorithms, letting readers understand the concepts quickly; Outlines an array of classifiers, various regression models, statistical tests and the techniques for pattern recognition using computational intelligence.

Download or read book Pattern Recognition and Neural Networks written by Brian D. Ripley and published by Cambridge University Press. This book was released on 2007 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 1996 book explains the statistical framework for pattern recognition and machine learning, now in paperback.

Download or read book Machine Learning in Image Analysis and Pattern Recognition written by Munish Kumar and published by MDPI. This book was released on 2021-09-08 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is to chart the progress in applying machine learning, including deep learning, to a broad range of image analysis and pattern recognition problems and applications. In this book, we have assembled original research articles making unique contributions to the theory, methodology and applications of machine learning in image analysis and pattern recognition.

Download or read book Computational Intelligence in Pattern Recognition written by Asit Kumar Das and published by Springer. This book was released on 2019-08-17 with total page 1046 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents practical development experiences in different areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.

Download or read book Image Pattern Recognition written by Svetlana N. Yanushkevich and published by World Scientific. This book was released on 2007 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of biometrics utilizes computer models of the physical and behavioral characteristics of human beings with a view to reliable personal identification. The human characteristics of interest include visual images, speech, and indeed anything which might help to uniquely identify the individual. The other side of the biometrics coin is biometric synthesis OCo rendering biometric phenomena from their corresponding computer models. For example, we could generate a synthetic face from its corresponding computer model. Such a model could include muscular dynamics to model the full gamut of human emotions conveyed by facial expressions. This book is a collection of carefully selected papers presenting the fundamental theory and practice of various aspects of biometric data processing in the context of pattern recognition. The traditional task of biometric technologies OCo human identification by analysis of biometric. data OCo is extended to include the new discipline of biometric synthesis."

Download or read book Parallel Processing for Artificial Intelligence 1 written by L.N. Kanal and published by Elsevier. This book was released on 2014-06-28 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge - methods which enable efficient and flexible processing of semantic networks are expected to have high utility for building large-scale knowledge-based systems. The third section explores the automatic parallel execution of production systems, which are used extensively in building rule-based expert systems - systems containing large numbers of rules are slow to execute and can significantly benefit from automatic parallel execution. The exploitation of parallelism for the mechanization of logic is dealt with in the fourth section. While sequential control aspects pose problems for the parallelization of production systems, logic has a purely declarative interpretation which does not demand a particular evaluation strategy. In this area, therefore, very large search spaces provide significant potential for parallelism. In particular, this is true for automated theorem proving. The fifth section considers the problem of constraint satisfaction, which is a useful abstraction of a number of important problems in AI and other fields of computer science. It also discusses the technique of consistent labeling as a preprocessing step in the constraint satisfaction problem. Section VI consists of two articles, each on a different, important topic. The first discusses parallel formulation for the Tree Adjoining Grammar (TAG), which is a powerful formalism for describing natural languages. The second examines the suitability of a parallel programming paradigm called Linda, for solving problems in artificial intelligence. Each of the areas discussed in the book holds many open problems, but it is believed that parallel processing will form a key ingredient in achieving at least partial solutions. It is hoped that the contributions, sourced from experts around the world, will inspire readers to take on these challenging areas of inquiry.