Structural, Syntactic, and Statistical Pattern Recognition, Ana Fred; Terry Caelli; Robert P.W. Duin; Aur?lio

Автор: Christopher M. Bishop
Название: Pattern Recognition and Machine Learning
ISBN: 0387310738 ISBN-13(EAN): 9780387310732
Издательство: Springer
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Описание: 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.

Автор: K.S. Fu; J.E. Albus; R.H. Anderson; J.M. Brayer; R
Название: Syntactic Pattern Recognition, Applications
ISBN: 3642664407 ISBN-13(EAN): 9783642664403
Издательство: Springer
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Описание: The many different mathematical techniques used to solve pattem recognition problems may be grouped into two general approaches: the decision-theoretic (or discriminant) approach and the syntactic (or structural) approach.

Автор: Petra Perner; Patrick Wang; Azriel Rosenfeld
Название: Advances in Structural and Syntactical Pattern Recognition
ISBN: 3540615776 ISBN-13(EAN): 9783540615774
Издательство: Springer
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Описание: The papers contained in this text are divided into sections on: grammars and languages; morphology and mathematical approaches to pattern recognition; semantic nets, relational models and graph-bassed methods; 2D and 3D shape recognition; and handwritten and printed character recognition.

Автор: Antonio Robles-Kelly; Marco Loog; Battista Biggio;
Название: Structural, Syntactic, and Statistical Pattern Recognition
ISBN: 3319490540 ISBN-13(EAN): 9783319490540
Издательство: Springer
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Описание: This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition, S+SSPR 2016, consisting of the International Workshop on Structural and Syntactic Pattern Recognition SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR.

Автор: Niels da Vitoria Lobo; Takis Kasparis; Michael Geo
Название: Structural, Syntactic, and Statistical Pattern Recognition
ISBN: 3540896880 ISBN-13(EAN): 9783540896883
Издательство: Springer
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Описание: Contains papers 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, and computer vision and biometrics.

Автор: Pasi Fr?nti; Gavin Brown; Marco Loog; Francisco Es
Название: Structural, Syntactic, and Statistical Pattern Recognition
ISBN: 3662444143 ISBN-13(EAN): 9783662444146
Издательство: Springer
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Описание: Graph Kernels.- A Graph Kernel from the Depth-Based Representation.- Incorporating Molecule's Stereoisomerism within the Machine Learning Framework.- Transitive State Alignment for the Quantum Jensen-Shannon Kernel.- Clustering.- Balanced K-Means for Clustering.- Poisoning Complete-Linkage Hierarchical Clustering.- A Comparison of Categorical Attribute Data Clustering Methods.- Graph Edit Distance.- Improving Approximate Graph Edit Distance Using Genetic Algorithms.- Approximate Graph Edit Distance Guided by Bipartite Matching of Bags of Walks.- A Hausdorff Heuristic for Efficient Computation of Graph Edit Distance.- Graph Models and Embedding.- Flip-Flop Sublinear Models for Graphs.- Node Centrality for Continuous-Time Quantum Walks.- Max-Correlation Embedding Computation.- Discriminant Analysis.- Fast Gradient Computation for Learning with Tensor Product Kernels and Sparse Training Labels.- Nonlinear Discriminant Analysis Based on Probability Estimation by Gaussian Mixture Model.- Combining and Selecting.- Information Theoretic Feature Selection in Multi-label Data through Composite Likelihood.- Majority Vote of Diverse Classifiers for Late Fusion.- Entropic Graph Embedding via Multivariate Degree Distributions.- On Parallel Lines in Noisy Forms.- Metrics and Dissimilarities.- Metric Learning in Dissimilarity Space for Improved Nearest Neighbor Performance.- Matching Similarity for Keyword-Based Clustering.- Applications.- Quantum vs Classical Ranking in Segment Grouping.- Remove Noise in Video with 3D Topological Maps.- Video Analysis of a Snooker Footage Based on a Kinematic Model.- Partial Supervision.- Evaluating Classification Performance with only Positive and Unlabeled Samples.- Who Is Missing? A New Pattern Recognition Puzzle.- Poster Session.- Edit Distance Computed by Fast Bipartite Graph Matching.- Statistical Method for Semantic Segmentation of Dominant Plane from Remote Exploration Image Sequence.- Analyses on Generalization Error of Ensemble Kernel Regressors.- Structural Human Shape Analysis for Modeling and Recognition.- On Cross-Validation for MLP Model Evaluation.- Weighted Mean Assignment of a Pair of Correspondences Using Optimisation Functions.- Chemical Symbol Feature Set for Handwritten Chemical Symbol Recognition.- About Combining Metric Learning and Prototype Generation.- Tracking System with Re-identification Using a RGB String Kernel.- Towards Scalable Prototype Selection by Genetic Algorithms with Fast Criteria.- IOWA Operators and Its Application to Image Retrieval.- On Optimum Thresholding of Multivariate Change Detectors.- Commute Time for a Gaussian Wave Packet on a Graph.- Properties of Object-Level Cross-Validation Schemes for Symmetric Pair-Input Data.- A Binary Factor Graph Model for Biclustering.- Improved BLSTM Neural Networks for Recognition of On-Line Bangla Complex Words.- A Ranking Part Model for Object Detection.- Regular Decomposition of Multivariate Time Series and Other Matrices.- Texture Synthesis: From Convolutional RBMs to Efficient Deterministic Algorithms.- Improved Object Matching Using Structural Relations.- Designing LDPC Codes for ECOC Classification Systems.- Unifying Probabilistic Linear Discriminant Analysis Variants in Biometric Authentication.

Автор: Edwin R. Hancock; Richard C Wilson; Terry Windeatt
Название: Structural, Syntactic, and Statistical Pattern Recognition
ISBN: 3642149790 ISBN-13(EAN): 9783642149795
Издательство: Springer
Цена: 18167.00 р.
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Описание: This volume in the Springer Lecture Notes in Computer Science (LNCS) series contains the papers presented at the S+SSPR 2010 Workshops, which was the seventh occasion that SPR and SSPR workshops have been held jointly. S+SSPR 2010 was organized by TC1 and TC2, Technical Committees of the International Association for Pattern Recognition(IAPR), andheld inCesme, Izmir, whichis a seaside resort on the Aegean coast of Turkey. The conference took place during August 18-20, 2010, only a few days before the 20th International Conference on Pattern Recognition (ICPR) which was held in Istanbul. The aim of the series of workshops is to create an international forum for the presentation of the latest results and exchange of ideas between researchers in the ?elds of statistical and structural pattern recognition. SPR 2010 and SSPR 2010 received a total of 99 paper submissions from many di?erent countries around the world, giving it a truly international perspective, as has been the case for previous S+SSPR workshops. This volume contains 70 accepted papers, 39 for oral and 31 for poster presentation. In addition to par- lel oral sessions for SPR and SSPR, there were two joint oral sessions of interest to both SPR and SSPR communities. Furthermore, to enhance the workshop experience, there were two joint panel sessions on "Structural Learning" and "Clustering," in which short author presentations were followed by discussion. Another innovation this year was the ?lming of the proceedings by Videol- tures.

Автор: Dit-Yan Yeung; James T. Kwok; Ana Fred; Fabio Roli
Название: Structural, Syntactic, and Statistical Pattern Recognition
ISBN: 3540372369 ISBN-13(EAN): 9783540372363
Издательство: Springer
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Описание: Constitutes 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.

Автор: Pesetsky, David
Название: Russian Case Morphology and the Syntactic Categories
ISBN: 026252502X ISBN-13(EAN): 9780262525022
Издательство: MIT Press
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Описание:

A proposal for a radical new view of case morphology, supported by a detailed investigation of some of the thorniest topics in Russian grammar.

In this book, David Pesetsky argues that the peculiarities of Russian nominal phrases provide significant clues concerning the syntactic side of morphological case. Pesetsky argues against the traditional view that case categories such as nominative or genitive have a special status in the grammar of human languages. Supporting his argument with a detailed analysis of a complex array of morpho-syntactic phenomena in the Russian noun phrase (with brief excursions to other languages), he proposes instead that the case categories are just part-of-speech features copied as morphology from head to dependent as syntactic structure is built.

Pesetsky presents a careful investigation of one of the thorniest topics in Russian grammar, the morpho-syntax of noun phrases with numerals (including those traditionally called the paucals). He argues that these bewilderingly complex facts can be explained if case categories are viewed simply as parts of speech, assigned as morphology. Pesetsky's analysis is notable for offering a new theoretical perspective on some of the most puzzling areas of Russian grammar, a highly original account of nominal case that significantly affects our understanding of an important property of language.

Автор: Boeckx
Название: Elementary Syntactic Structures
ISBN: 1107034094 ISBN-13(EAN): 9781107034099
Издательство: Cambridge Academ
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Описание: Turning grammar upside down, this book proposes a new model of syntax that is better suited for interdisciplinary interactions, and shows how syntax can proceed free of lexical influence. The empirical domain examined is vast, and all the fundamental units and properties of syntax are rethought.

Автор: Terry Caelli; Adnan Amin; Robert P.W. Duin; Mohame
Название: Structural, Syntactic, and Statistical Pattern Recognition
ISBN: 3540440119 ISBN-13(EAN): 9783540440116
Издательство: Springer
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Описание: Constitutes the proceedings of the 9th International Workshop on Structural and Syntactic Pattern Recognition and the 4th International Workshop on Statistical Techniques in Pattern Recognition held in Canada in 2002.

Автор: Gabriel Ferrate; Theo Pavlidis; Alberto Sanfeliu;
Название: Syntactic and Structural Pattern Recognition
ISBN: 3642834647 ISBN-13(EAN): 9783642834646
Издательство: Springer
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Описание: Proceedings of the NATO Advanced Research Workshop on Syntactic and Structural Pattern Recognition, held in Barcelona-Sitges, Spain, October 23-25, 1986