Pattern Recognition and Information Processing

Pattern Recognition and Information Processing PDF Author: Sergey V. Ablameyko
Publisher: Springer Nature
ISBN: 303035430X
Category : Computers
Languages : en
Pages : 320

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Book Description
This book constitutes the refereed proceedings of the 14th International Conference on Pattern Recognition and Information Processing, PRIP 2019, held in Minsk, Belarus, in May 2019. The 25 revised full papers were carefully reviewed and selected from 120 submissions. The papers of this volume are organized in topical sections on pattern recognition and image analysis; information processing and applications.

Pattern Recognition and Information Processing

Pattern Recognition and Information Processing PDF Author: Sergey V. Ablameyko
Publisher: Springer Nature
ISBN: 303035430X
Category : Computers
Languages : en
Pages : 320

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Book Description
This book constitutes the refereed proceedings of the 14th International Conference on Pattern Recognition and Information Processing, PRIP 2019, held in Minsk, Belarus, in May 2019. The 25 revised full papers were carefully reviewed and selected from 120 submissions. The papers of this volume are organized in topical sections on pattern recognition and image analysis; information processing and applications.

Psychological Processes in Pattern Recognition

Psychological Processes in Pattern Recognition PDF Author: Stephen K. Reed
Publisher: Academic Press
ISBN: 1483263347
Category : Psychology
Languages : en
Pages : 261

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Book Description
Psychological Processes in Pattern Recognition describes information-processing models of pattern recognition. This book is organized into five parts encompassing 11 chapters that particularly focus on visual pattern recognition and the many issues relevant to a more general theory of pattern recognition. The first three parts cover the representation, temporal effects, and memory codes of pattern recognition. These parts include the features, templates, schemata, and structural descriptions of information processing models. The principles of parallel matching, iconic storage, and the components and networks of memory codes are also considered. The remaining two parts look into the perceptual classification and response selection of pattern recognition. These parts specifically tackle the development of probability, distance, and recognition models. This book is intended primarily for psychologists, graduate students, and researchers who are interested in the problems of pattern recognition and human information processing.

Data Complexity in Pattern Recognition

Data Complexity in Pattern Recognition PDF Author: Mitra Basu
Publisher: Springer Science & Business Media
ISBN: 1846281725
Category : Computers
Languages : en
Pages : 309

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Book Description
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.

Pattern Recognition in Speech and Language Processing

Pattern Recognition in Speech and Language Processing PDF Author: Wu Chou
Publisher: CRC Press
ISBN: 0203010523
Category : Technology & Engineering
Languages : en
Pages : 413

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Book Description
Over the last 20 years, approaches to designing speech and language processing algorithms have moved from methods based on linguistics and speech science to data-driven pattern recognition techniques. These techniques have been the focus of intense, fast-moving research and have contributed to significant advances in this field. Pattern Reco

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning PDF Author: King-Sun Fu
Publisher: Springer Science & Business Media
ISBN: 1461575664
Category : Computers
Languages : en
Pages : 350

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Book Description
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.

Information Theory in Computer Vision and Pattern Recognition

Information Theory in Computer Vision and Pattern Recognition PDF Author: Francisco Escolano Ruiz
Publisher: Springer Science & Business Media
ISBN: 1848822979
Category : Computers
Languages : en
Pages : 375

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Book Description
Information theory has proved to be effective for solving many computer vision and pattern recognition (CVPR) problems (such as image matching, clustering and segmentation, saliency detection, feature selection, optimal classifier design and many others). Nowadays, researchers are widely bringing information theory elements to the CVPR arena. Among these elements there are measures (entropy, mutual information...), principles (maximum entropy, minimax entropy...) and theories (rate distortion theory, method of types...). This book explores and introduces the latter elements through an incremental complexity approach at the same time where CVPR problems are formulated and the most representative algorithms are presented. Interesting connections between information theory principles when applied to different problems are highlighted, seeking a comprehensive research roadmap. The result is a novel tool both for CVPR and machine learning researchers, and contributes to a cross-fertilization of both areas.

Adaptive Pattern Recognition and Neural Networks

Adaptive Pattern Recognition and Neural Networks PDF Author: Yoh-Han Pao
Publisher: Addison Wesley Publishing Company
ISBN:
Category : Computers
Languages : en
Pages : 344

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Book Description
A coherent introduction to the basic concepts of pattern recognition, incorporating recent advances from AI, neurobiology, engineering, and other disciplines. Treats specifically the implementation of adaptive pattern recognition to neural networks. Annotation copyright Book News, Inc. Portland, Or.

Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning PDF Author: Christopher M. Bishop
Publisher: Springer
ISBN: 9781493938438
Category : Computers
Languages : en
Pages : 0

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Book Description
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.

Pattern Recognition

Pattern Recognition PDF Author: Sergios Theodoridis
Publisher: Elsevier
ISBN: 008051362X
Category : Technology & Engineering
Languages : en
Pages : 705

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Book Description
Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to "learn" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10 years of teaching experience, the text was developed by the authors through use in their own classrooms.*Approaches pattern recognition from the designer's point of view*New edition highlights latest developments in this growing field, including independent components and support vector machines, not available elsewhere*Supplemented by computer examples selected from applications of interest

Image Processing and Pattern Recognition

Image Processing and Pattern Recognition PDF Author: Frank Y. Shih
Publisher: John Wiley & Sons
ISBN: 0470404612
Category : Technology & Engineering
Languages : en
Pages : 564

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Book Description
A comprehensive guide to the essential principles of image processing and pattern recognition Techniques and applications in the areas of image processing and pattern recognition are growing at an unprecedented rate. Containing the latest state-of-the-art developments in the field, Image Processing and Pattern Recognition presents clear explanations of the fundamentals as well as the most recent applications. It explains the essential principles so readers will not only be able to easily implement the algorithms and techniques, but also lead themselves to discover new problems and applications. Unlike other books on the subject, this volume presents numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. Scores of graphs and examples, technical assistance, and practical tools illustrate the basic principles and help simplify the problems, allowing students as well as professionals to easily grasp even complicated theories. It also features unique coverage of the most interesting developments and updated techniques, such as image watermarking, digital steganography, document processing and classification, solar image processing and event classification, 3-D Euclidean distance transformation, shortest path planning, soft morphology, recursive morphology, regulated morphology, and sweep morphology. Additional topics include enhancement and segmentation techniques, active learning, feature extraction, neural networks, and fuzzy logic. Featuring supplemental materials for instructors and students, Image Processing and Pattern Recognition is designed for undergraduate seniors and graduate students, engineering and scientific researchers, and professionals who work in signal processing, image processing, pattern recognition, information security, document processing, multimedia systems, and solar physics.