Advances In Structural And Syntactical Pattern Recognition

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Advances in Structural and Syntactical Pattern Recognition

Author : Petra Perner,Patrick Wang
Publisher : Springer Science & Business Media
Page : 412 pages
File Size : 43,9 Mb
Release : 1996-08-07
Category : Computers
ISBN : 3540615776

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Advances in Structural and Syntactical Pattern Recognition by Petra Perner,Patrick Wang Pdf

This book constitutes the refereed proceedings of the 6th International Workshop on Structural and Syntactical Pattern Recognition, SSPR '96, held in Leipzig, Germany in August 1996. The 36 revised full papers included together with three invited papers were carefully selected from a total of 52 submissions. The papers are organized in topical sections on grammars and languages; morphology and mathematical approaches to pattern recognition; semantic nets, relational models and graph-based methods; 2D and 3D shape recognition; document image analysis and recognition; and handwritten and printed character recognition.

Advances in Structural and Syntactic Pattern Recognition

Author : H Bunke
Publisher : World Scientific
Page : 636 pages
File Size : 47,7 Mb
Release : 1993-02-23
Category : Electronic
ISBN : 9789814505154

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Advances in Structural and Syntactic Pattern Recognition by H Bunke Pdf

Pattern recognition is an active area of research with many applications, some of which have reached commercial maturity. Structural and syntactic methods are very powerful. They are based on symbolic data structures together with matching, parsing, and reasoning procedures that are able to infer interpretations of complex input patterns. This book gives an overview of the latest developments and achievements in the field. Contents:Recent Advances in String Matching (H Bunke)A New Efficient Method to Represent and Process Proximity and Similarity in Sets of Complex Objects (H Noltemeier)A Quick Way for Relational Matching: Morphology (R M Haralick et al.)Understanding Neural Networks for Grammatical Inference and Recognition (A Sanfeliu & R Alquezar)Some Recent Results on Stochastic Language Modelling (A Corazza et al.)Background Structure in Document Images (H S Baird)Automatic Object Modelization in Computer Vision (P Gros & R Mohr)Object Recognition by a Robust Matching Technique (R Salzbrunn et al.)PDL-HM: Morphological and Syntactic Shape Classification Algorithm. Real-Time Application to Fish Species Classification (H Arnarson & L F Pau et al.)Selection of Landmarks Based Upon 3D and Iconic Properties (S Tsuji & S Tsuji)and other papers Readership: Computer scientists. keywords:

Syntactic and Structural Pattern Recognition

Author : Horst Bunke,Alberto Sanfeliu
Publisher : World Scientific
Page : 568 pages
File Size : 50,6 Mb
Release : 1990
Category : Computers
ISBN : 9971505665

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Syntactic and Structural Pattern Recognition by Horst Bunke,Alberto Sanfeliu Pdf

This book is currently the only one on this subject containing both introductory material and advanced recent research results. It presents, at one end, fundamental concepts and notations developed in syntactic and structural pattern recognition and at the other, reports on the current state of the art with respect to both methodology and applications. In particular, it includes artificial intelligence related techniques, which are likely to become very important in future pattern recognition.The book consists of individual chapters written by different authors. The chapters are grouped into broader subject areas like “Syntactic Representation and Parsing”, “Structural Representation and Matching”, “Learning”, etc. Each chapter is a self-contained presentation of one particular topic. In order to keep the original flavor of each contribution, no efforts were undertaken to unify the different chapters with respect to notation. Naturally, the self-containedness of the individual chapters results in some redundancy. However, we believe that this handicap is compensated by the fact that each contribution can be read individually without prior study of the preceding chapters. A unification of the spectrum of material covered by the individual chapters is provided by the subject and author index included at the end of the book.

Advances in Pattern Recognition

Author : Francesc J. Ferri,Jose M. Inesta,Adnan Amin,Pavel Pudil
Publisher : Springer
Page : 0 pages
File Size : 55,5 Mb
Release : 2003-06-26
Category : Computers
ISBN : 3540445226

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Advances in Pattern Recognition by Francesc J. Ferri,Jose M. Inesta,Adnan Amin,Pavel Pudil Pdf

This book constitutes the joint refereed proceedings of the 8th International Workshop on Structural and Syntactic Pattern Recognition and the 3rd International Workshop on Statistical Techniques in Pattern Recognition, SSPR 2000 and SPR 2000, held in Alicante, Spain in August/September 2000. The 52 revised full papers presented together with five invited papers and 35 posters were carefully reviewed and selected from a total of 130 submissions. The book offers topical sections on hybrid and combined methods, document image analysis, grammar and language methods, structural matching, graph-based methods, shape analysis, clustering and density estimation, object recognition, general methodology, and feature extraction and selection.

Advances in Pattern Recognition

Author : Adnan Amin,Dov Dori,Pavel Pudil,Herbert Freeman
Publisher : Springer Science & Business Media
Page : 1084 pages
File Size : 40,8 Mb
Release : 1998-07-29
Category : Computers
ISBN : 3540648585

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Advances in Pattern Recognition by Adnan Amin,Dov Dori,Pavel Pudil,Herbert Freeman Pdf

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Advances in Pattern Recognition

Author : Francesc J. Ferri,Jose M. Inesta,Adnan Amin,Pavel Pudil
Publisher : Springer Science & Business Media
Page : 918 pages
File Size : 40,6 Mb
Release : 2000-08-23
Category : Computers
ISBN : 9783540679462

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Advances in Pattern Recognition by Francesc J. Ferri,Jose M. Inesta,Adnan Amin,Pavel Pudil Pdf

This book constitutes the joint refereed proceedings of the 8th International Workshop on Structural and Syntactic Pattern Recognition and the 3rd International Workshop on Statistical Techniques in Pattern Recognition, SSPR 2000 and SPR 2000, held in Alicante, Spain in August/September 2000. The 52 revised full papers presented together with five invited papers and 35 posters were carefully reviewed and selected from a total of 130 submissions. The book offers topical sections on hybrid and combined methods, document image analysis, grammar and language methods, structural matching, graph-based methods, shape analysis, clustering and density estimation, object recognition, general methodology, and feature extraction and selection.

Structural, Syntactic, and Statistical Pattern Recognition

Author : Terry Caelli,Adnan Amin,Robert P.W. Duin,Mohamed Kamel,Dick de Ridder
Publisher : Springer
Page : 866 pages
File Size : 43,8 Mb
Release : 2003-08-02
Category : Computers
ISBN : 9783540706595

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Structural, Syntactic, and Statistical Pattern Recognition by Terry Caelli,Adnan Amin,Robert P.W. Duin,Mohamed Kamel,Dick de Ridder Pdf

This volume contains all papers presented at SSPR 2002 and SPR 2002 hosted by the University of Windsor, Windsor, Ontario, Canada, August 6-9, 2002. This was the third time these two workshops were held back-to-back. SSPR was the ninth International Workshop on Structural and Syntactic Pattern Recognition and the SPR was the fourth International Workshop on Statis- cal Techniques in Pattern Recognition. These workshops have traditionally been held in conjunction with ICPR (International Conference on Pattern Recog- tion), and are the major events for technical committees TC2 and TC1, resp- tively, of the International Association of Pattern Recognition (IAPR). The workshops were held in parallel and closely coordinated. This was an attempt to resolve the dilemma of how to deal, in the light of the progressive specialization of pattern recognition, with the need for narrow-focus workshops without further fragmenting the ?eld and introducing yet another conference that would compete for the time and resources of potential participants. A total of 116 papers were received from many countries with the submission and reviewingprocesses beingcarried out separately for each workshop. A total of 45 papers were accepted for oral presentation and 35 for posters. In addition four invited speakers presented informative talks and overviews of their research. They were: Tom Dietterich, Oregon State University, USA Sven Dickinson, the University of Toronto, Canada Edwin Hancock, University of York, UK Anil Jain, Michigan State University, USA SSPR 2002 and SPR 2002 were sponsored by the IAPR and the University of Windsor.

Syntactic and Structural Pattern Recognition

Author : Gabriel Ferrate,Theo Pavlidis,Alberto Sanfeliu,Horst Bunke
Publisher : Springer Science & Business Media
Page : 456 pages
File Size : 42,7 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642834622

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Syntactic and Structural Pattern Recognition by Gabriel Ferrate,Theo Pavlidis,Alberto Sanfeliu,Horst Bunke Pdf

Thirty years ago pattern recognition was dominated by the learning machine concept: that one could automate the process of going from the raw data to a classifier. The derivation of numerical features from the input image was not considered an important step. One could present all possible features to a program which in turn could find which ones would be useful for pattern recognition. In spite of significant improvements in statistical inference techniques, progress was slow. It became clear that feature derivation was a very complex process that could not be automated and that features could be symbolic as well as numerical. Furthennore the spatial relationship amongst features might be important. It appeared that pattern recognition might resemble language analysis since features could play the role of symbols strung together to form a word. This led. to the genesis of syntactic pattern recognition, pioneered in the middle and late 1960's by Russel Kirsch, Robert Ledley, Nararimhan, and Allan Shaw. However the thorough investigation of the area was left to King-Sun Fu and his students who, until his untimely death, produced most of the significant papers in this area. One of these papers (syntactic recognition of fingerprints) received the distinction of being selected as the best paper published that year in the IEEE Transaction on Computers. Therefore syntactic pattern recognition has a long history of active research and has been used in industrial applications.

Structural, Syntactic, and Statistical Pattern Recognition

Author : Dit-Yan Yeung
Publisher : Springer Science & Business Media
Page : 959 pages
File Size : 54,9 Mb
Release : 2006-08-03
Category : Computers
ISBN : 9783540372363

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Structural, Syntactic, and Statistical Pattern Recognition by Dit-Yan Yeung Pdf

This is the proceedings of the 11th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2006 and the 6th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2006, held in Hong Kong, August 2006 alongside the Conference on Pattern Recognition, ICPR 2006. 38 revised full papers and 61 revised poster papers are included, together with 4 invited papers covering image analysis, character recognition, bayesian networks, graph-based methods and more.

Pattern Recognition

Author : J.P. Marques de Sá
Publisher : Springer Science & Business Media
Page : 331 pages
File Size : 51,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642566516

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Pattern Recognition by J.P. Marques de Sá Pdf

The book provides a comprehensive view of pattern recognition concepts and methods, illustrated with real-life applications in several areas. A CD-ROM offered with the book includes datasets and software tools, making it easier to follow in a hands-on fashion, right from the start.

Advances in Pattern Recognition - ICAPR 2001

Author : Sameer Singh,Nabeel Murshed,Walter Kropatsch
Publisher : Springer
Page : 482 pages
File Size : 48,6 Mb
Release : 2003-06-29
Category : Computers
ISBN : 9783540447320

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Advances in Pattern Recognition - ICAPR 2001 by Sameer Singh,Nabeel Murshed,Walter Kropatsch Pdf

The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation quality; Section 5 concludes this paper. 2. The norm-orientation-discontinuity interfering stroke model Figure 2 shows three typical samples of original image segments from the original documents and their magnitude of the detected edges respectively. The magnitude of the gradient is converted into the gray level value. The darker the edge is, the larger is the gradient magnitude. It is obvious that the topmost strong edges correspond to foreground edges. It should be noted that, while usually, the foreground writing appears darker than the background image, as shown in sample image Figure 2(a), there are cases where the foreground and background have similar intensities as shown in Figure 2(b), or worst still, the background is more prominent than the foreground as in Figure 2(c). So using only the intensity value is not enough to differentiate the foreground from the background. (a) (b) (c) (d) (e) (f)

Structural, Syntactic, and Statistical Pattern Recognition

Author : Georgy Gimel ́farb,Edwin Hancock,Atsushi Imiya,Arjan Kuijper,Mineichi Kudo,Shinichiro Omachi,Terry Windeatt,Keiji Yamada
Publisher : Springer
Page : 770 pages
File Size : 54,7 Mb
Release : 2012-10-22
Category : Computers
ISBN : 9783642341663

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Structural, Syntactic, and Statistical Pattern Recognition by Georgy Gimel ́farb,Edwin Hancock,Atsushi Imiya,Arjan Kuijper,Mineichi Kudo,Shinichiro Omachi,Terry Windeatt,Keiji Yamada Pdf

This volume constitutes the refereed proceedings of the Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012), held in Hiroshima, Japan, in November 2012 as a satellite event of the 21st International Conference on Pattern Recognition, ICPR 2012. The 80 revised full papers presented together with 1 invited paper and the Pierre Devijver award lecture were carefully reviewed and selected from more than 120 initial submissions. The papers are organized in topical sections on structural, syntactical, and statistical pattern recognition, graph and tree methods, randomized methods and image analysis, kernel methods in structural and syntactical pattern recognition, applications of structural and syntactical pattern recognition, clustering, learning, kernel methods in statistical pattern recognition, kernel methods in statistical pattern recognition, as well as applications of structural, syntactical, and statistical methods.

Structural, Syntactic, and Statistical Pattern Recognition

Author : Ana Fred,Terry Caelli,Robert P.W. Duin,Aurélio Campilho,Dick de Ridder
Publisher : Springer
Page : 1169 pages
File Size : 55,7 Mb
Release : 2004-10-29
Category : Computers
ISBN : 9783540278689

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Structural, Syntactic, and Statistical Pattern Recognition by Ana Fred,Terry Caelli,Robert P.W. Duin,Aurélio Campilho,Dick de Ridder Pdf

This volume contains all papers presented at SSPR 2004 and SPR 2004, hosted by the Instituto de Telecomunicac ̃ ̧oes/Instituto Superior T ́ ecnico, Lisbon, Portugal, August 18-20, 2004. This was the fourth time that the two workshops were held back-to-back. The SSPR was the tenth International Workshop on Structural and Synt- tic Pattern Recognition, and the SPR was the ?fth International Workshop on Statistical Techniques in Pattern Recognition. These workshops have traditi- ally been held in conjunction with ICPR (International Conference on Pattern Recognition), and are the major events for technical committees TC2 and TC1, respectively, of the International Association for Pattern Recognition (IAPR). The workshops were closely coordinated, being held in parallel, with plenary talks and a common session on hybrid systems. This was an attempt to resolve thedilemmaofhowto dealwiththeneedfornarrow-focusspecializedworkshops yet accommodate the presentation of new theories and techniques that blur the distinction between the statistical and the structural approaches. A total of 219 papers were received from many countries, with the subm- sion and reviewing processes being carried out separately for each workshop. A total of 59 papers were accepted for oral presentation and 64 for posters. In - dition, four invited speakers presented informative talks and overviews of their research. They were: Alberto Sanfeliu, from the Technical University of Cata- nia, Spain; Marco Gori, from the University of Siena, Italy; Nello Cristianini, from the University of California, USA; and Erkki Oja, from Helsinki University of Technology, Finland, winner of the 2004 Pierre Devijver Award.

Structural, Syntactic, and Statistical Pattern Recognition

Author : Niels da Vitoria Lobo
Publisher : Springer Science & Business Media
Page : 1029 pages
File Size : 47,8 Mb
Release : 2008-11-24
Category : Computers
ISBN : 9783540896883

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Structural, Syntactic, and Statistical Pattern Recognition by Niels da Vitoria Lobo Pdf

This book constitutes the refereed proceedings of the 12th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2008 and the 7th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2008, held jointly in Orlando, FL, USA, in December 2008 as a satellite event of the 19th International Conference of Pattern Recognition, ICPR 2008. The 56 revised full papers and 42 revised poster papers presented together with the abstracts of 4 invited papers were carefully reviewed and selected from 175 submissions. The papers are organized in topical sections on graph-based methods, probabilistic and stochastic structural models for PR, image and video analysis, shape analysis, kernel methods, recognition and classification, applications, ensemble methods, feature selection, density estimation and clustering, computer vision and biometrics, pattern recognition and applications, pattern recognition, as well as feature selection and clustering.