Syntactic Pattern Recognition for Seismic Oil Exploration
Syntactic Pattern Recognition for Seismic Oil Exploration

Author: Kou-Yuan Huang

Publisher: World Scientific

Published: 2002-01-01

Total Pages: 152

ISBN-13: 9789812775740

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The use of pattern recognition has become more and more important in seismic oil exploration. Interpreting a large volume of seismic data is a challenging problem. Seismic reflection data in the one-shot seismogram and stacked seismogram may contain some structural information from the response of the subsurface. Syntactic/structural pattern recognition techniques can recognize the structural seismic patterns and improve seismic interpretations. The syntactic analysis methods include: (1) the error-correcting finite-state parsing, (2) the modified error-correcting Earley's parsing, (3) the parsing using the match primitive measure, (4) the Levenshtein distance computation, (5) the likelihood ratio test, (6) the error-correcting tree automata, and (7) a hierarchical system. Syntactic seismic pattern recognition can be one of the milestones of a geophysical intelligent interpretation system. The syntactic methods in this book can be applied to other areas, such as the medical diagnosis system. The book will benefit geophysicists, computer scientists and electrical engineers. Sample Chapter(s). Chapter 1: Introduction to Syntactic Pattern Recognition (114 KB). Contents: Introduction to Syntactic Pattern Recognition; Introduction to Formal Languages and Automata; Error-Correcting Finite-State Automaton for Recognition of Ricker Wavelets; Attributed Grammar and Error-Correcting Earley's Parsing; Attributed Grammar and Match Primitive Measure (MPM) for Recognition of Seismic Wavelets; String Distance and Likelihood Ratio Test for Detection of Candidate Bright Spot; Tree Grammar and Automaton for Seismic Pattern Recognition; A Hierarchical Recognition System of Seismic Patterns and Future Study. Readership: Geophysicists, computer scientists and electrical engineers.

Syntactic Pattern Recognition For Seismic Oil Exploration
Syntactic Pattern Recognition For Seismic Oil Exploration

Author: Kou-yuan Huang

Publisher: World Scientific

Published: 2002-05-08

Total Pages: 149

ISBN-13: 9814491195

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The use of pattern recognition has become more and more important in seismic oil exploration. Interpreting a large volume of seismic data is a challenging problem. Seismic reflection data in the one-shot seismogram and stacked seismogram may contain some structural information from the response of the subsurface. Syntactic/structural pattern recognition techniques can recognize the structural seismic patterns and improve seismic interpretations.The syntactic analysis methods include: (1) the error-correcting finite-state parsing, (2) the modified error-correcting Earley's parsing, (3) the parsing using the match primitive measure, (4) the Levenshtein distance computation, (5) the likelihood ratio test, (6) the error-correcting tree automata, and (7) a hierarchical system.Syntactic seismic pattern recognition can be one of the milestones of a geophysical intelligent interpretation system. The syntactic methods in this book can be applied to other areas, such as the medical diagnosis system. The book will benefit geophysicists, computer scientists and electrical engineers.

Syntactic Pattern Recognition
Syntactic Pattern Recognition

Author: Mariusz Flasinski

Publisher: World Scientific

Published: 2019-03-25

Total Pages: 403

ISBN-13: 981327848X

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This unique compendium presents the major methods of recognition and learning used in syntactic pattern recognition from the 1960s till 2018. Each method is introduced firstly in a formal way. Then, it is explained with the help of examples and its algorithms are described in a pseudocode. The survey of the applications contains more than 1,000 sources published since the 1960s. The open problems in the field, the challenges and the determinants of the future development of syntactic pattern recognition are discussed.This must-have volume provides a good read and serves as an excellent source of reference materials for researchers, academics, and postgraduate students in the fields of pattern recognition, machine perception, computer vision and artificial intelligence.

Seismic Modelling and Pattern Recognition in Oil Exploration
Seismic Modelling and Pattern Recognition in Oil Exploration

Author: A. Sinvhal

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 199

ISBN-13: 9401125708

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The reasons for writing this book are very simple. We use and teach com puter aided techniques of mathematical simulation and of pattern recogni tion. Life would be much simpler if we had a suitable text book with methods and computer programmes which we could keep referring to. Therefore, we have presented here material that is essential for mathematical modelling of some complex geological situations, with which earth scientists are often confronted. The reader is introduced not only to the essentials of computer modelling, data analysis and pattern recognition, but is also made familiar with the basic understanding with which they can plunge into when solving related and more complex problems. This book first makes a case for seismic stratigraphy and then for pattern recognition. Chapter 1 provides an extensive review of applications of pattern recognition methods in oil exploration. Simulation procedures are presented with examples that are fairly simple to understand and easy to use on the computer. Several geological situations can be formulated and simulated using the Monte Carlo method. The binary lithologic sequences, discussed in Chapter 2, consist of alternating layers of any two of sand, shale and coal.

Progress on Pattern Classification, Image Processing and Communications
Progress on Pattern Classification, Image Processing and Communications

Author: Robert Burduk

Publisher: Springer Nature

Published: 2023-11-30

Total Pages: 241

ISBN-13: 3031416309

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This book presents a collection of high-quality research papers accepted to multi-conference consisting of the 13th International Conference on Image Processing and Communications (IP&C 2023), the 13th International Conference on Computer Recognition Systems (CORES 2023) held jointly in Wroclaw, Poland (virtually), in June 2023. The accepted papers address current computer science and computer systems-related technological challenges and solutions, as well as many practical applications and results. The first part of the book deals with advances in pattern recognition and classifiers, the second part is devoted to image processing and computer vision, while the third part addresses practical applications of computer recognition systems. We believe this book will be interesting for researchers and practitioners in many fields of computer science and IT applications.

Automated Pattern Analysis in Petroleum Exploration
Automated Pattern Analysis in Petroleum Exploration

Author: Ibrahim Palaz

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 315

ISBN-13: 1461243882

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Here is a state-of-the-art survey of artificial intelligence in modern exploration programs. Focussing on standard exploration procedures, the contributions examine the advantages and pitfalls of using these new techniques, and, in the process, provide new, more accurate and consistent methods for solving old problems. They show how expert systems can provide the integration of information that is essential in the petroleum industry when solving the complicated questions facing the modern petroleum geoscientist.

Hybrid Methods in Pattern Recognition
Hybrid Methods in Pattern Recognition

Author: Horst Bunke

Publisher: World Scientific

Published: 2002

Total Pages: 338

ISBN-13: 9810248326

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The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system. Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data structures, hybrid methods in data mining, the combination of symbolic and subsymbolic learning, and so on. Also included is recent work on multiple classifier systems. Furthermore, the book deals with applications in on-line and off-line handwriting recognition, remotely sensed image interpretation, fingerprint identification, and automatic text categorization.

Soft Computing Approach Pattern Recognition And Image Processing
Soft Computing Approach Pattern Recognition And Image Processing

Author: Ashish Ghosh

Publisher: World Scientific

Published: 2002-11-25

Total Pages: 371

ISBN-13: 981448685X

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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.

Soft Computing Approach to Pattern Recognition and Image Processing
Soft Computing Approach to Pattern Recognition and Image Processing

Author: Ashish Ghosh

Publisher: World Scientific

Published: 2002

Total Pages: 371

ISBN-13: 9812382518

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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.

Handbook of Pattern Recognition and Computer Vision
Handbook of Pattern Recognition and Computer Vision

Author: C. H. Chen

Publisher: World Scientific

Published: 1993-08

Total Pages: 1000

ISBN-13: 9789810222765

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"The book provides an up-to-date and authoritative treatment of pattern recognition and computer vision, with chapters written by leaders in the field. On the basic methods in pattern recognition and computer vision, topics range from statistical pattern recognition to array grammars to projective geometry to skeletonization, and shape and texture measures."--BOOK JACKET.