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[null,"1.","Record Nr.",null,"UNINA9910459143403321"]
[null,null,"Autore",null,"Operstein Natalie"]
[null,null,"Titolo",null,"Consonant structure and prevocalization [[electronic resource] /] / Natalie Operstein"]
[null,null,"Pubbl/distr/stampa",null,"Philadelphia, PA, : John Benjamins, 2010"]
[null,null,"ISBN",null,"1-281-04258-7"]
[{"$nulls":4},"9786613773579"]
[{"$nulls":4},"90-272-9090-3"]
[null,null,"Descrizione fisica",null,"1 online resource (244 p.)"]
[null,null,"Collana",null,"Current issues in linguistic theory, , 0304-0763 ; ; 312"]
[null,null,"Disciplina",null,"414"]
[null,null,"Soggetti",null,"Consonants"]
[{"$nulls":4},"Grammar, Comparative and general - Phonology"]
[{"$nulls":4},"Vowels"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Consonant Structure and Prevocalization; Editorial page; Title page; LCC page; Table of contents; Preface & acknowledgments; Part 1. The theory; Chapter 1. Consonant prevocalization; 1.1 Goals and organization of the study; 1.2 Data and definitions; 1.3 Conditioning factors; 1.4 CP and vowel diphthongization; 1.5 Toward a theory of CP; 1.6 Theoretical approaches; 1.6.1 Vocalization of primary stricture; 1.6.2 Vowel diphthongization; 1.7 Summary and conclusion; Chapter 2. Intrasegmental consonant structure; 2.1 Preliminaries; 2.2 The analytical framework"]
[{"$nulls":4},"2.3 CP and the bigestural structure of consonants2.3.1 Intrasegmental gestures; 2.3.2 CP of secondarily modified consonants; 2.3.3 CP of plain consonants; 2.4 Summary and outlook; Chapter 3. Related processes; 3.1 Introduction; 3.2 Consonant postvocalization; 3.3 Syllabic consonants; 3.4 Alternatives to CP; 3.4.1 Vowel intrusion; 3.4.2 (Compensatory) vowel lengthening; 3.5 Summary and outlook; Part 2. The data; Chapter 4. Front prevowels; 4.1 Introduction; 4.2 Palatalized consonants; 4.2.1 Preliminary considerations; 4.2.2 Contrastively palatalized consonants"]
[{"$nulls":4},"4.2.3 Contextually palatalized consonants4.2.4 Palatal umlaut; 4.3 Palatals; 4.3.1 Preliminary considerations; 4.3.2 Catalan, French, Portuguese; 4.3.3 English; 4.3.4 Other languages; 4.3.5 Palatals in "]
[{"$nulls":4},"loanwords; 4.4 Alveolars; 4.4.1 Liquids; 4.4.2 /s/; 4.4.3 /n/; 4.4.4 Word-final weakening; 4.5 Summary and conclusion; Chapter 5. Other prevowels; 5.1 Introduction; 5.2 Prevelarization and prelabialization; 5.2.1 Dentals; 5.2.2 Dark [ł]; 5.2.3 Velar nasal; 5.2.4 Broad consonants in Gaelic; 5.2.5 Back umlaut and breaking; 5.2.6 Labial and labialized consonants; 5.3 Postvelar consonants"]
[{"$nulls":4},"5.4 Retroflex consonants5.5 Summary and conclusion; Chapter 6. Conclusions and outlook; References; Appendix 1. Rosapelly's vocaloid; Appendix 2. Languages in the survey; Index of languages; Index of subjects and terms"]
[null,null,null,"Sommario/riassunto","This monograph proposes a new interpretation of the intrasegmental structure of consonants and provides the first systematic intra- and cross-linguistic study of consonant prevocalization. The proposed model represents consonants as inherently bigestural and makes strong predictions that are automatically relevant to phonological theory at both the diachronic and synchronic levels, and also to the phonetics of articulatory evolution. It also clearly demonstrates that a wide generalization of the notion of consonant prevocalization provides a uniform account for many well-known processes genera"]
[null,"2.","Record Nr.",null,"UNINA9910815468903321"]
[null,null,"Autore",null,"Cyganek Bogusław"]
[null,null,"Titolo",null,"Object detection and recognition in digital images : theory and practice / / Bogusław Cyganek"]
[null,null,"Pubbl/distr/stampa",null,"Chichester, West Sussex, U.K., : John Wiley & Sons, Inc., 2013"]
[null,null,"ISBN",null,"9781118618363"]
[{"$nulls":4},"111861836X"]
[{"$nulls":4},"9781118618387"]
[{"$nulls":4},"1118618386"]
[{"$nulls":4},"9781118618370"]
[{"$nulls":4},"1118618378"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (552 p.)"]
[null,null,"Disciplina",null,"621.39/94"]
[null,null,"Soggetti",null,"Pattern recognition systems"]
[{"$nulls":4},"Image processing - Digital techniques"]
[{"$nulls":4},"Computer vision"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"OBJECT DETECTION AND RECOGNITION IN DIGITAL IMAGES; Contents; Preface; Acknowledgements; Notations and Abbreviations; 1 Introduction; 1.1 A Sample of Computer Vision; 1.2 Overview of Book Contents; References; 2 Tensor Methods in Computer Vision; 2.1 Abstract; 2.2 Tensor - A Mathematical Object; 2.2.1 Main Properties of Linear Spaces; 2.2.2 Concept of a Tensor; 2.3 Tensor - A Data Object; 2.4 Basic Properties of Tensors; 2.4.1 Notation of Tensor Indices and Components; 2.4.2 Tensor Products; 2.5 Tensor Distance Measures; 2.5.1 Overview of Tensor Distances"]
[{"$nulls":4},"2.5.1.1 Computation of Matrix Exponent and Logarithm Functions2.5.2 Euclidean Image Distance and Standardizing Transform; 2.6 Filtering of Tensor Fields; 2.6.1 Order Statistic Filtering of Tensor Data; 2.6.2 Anisotropic Diffusion Filtering; 2.6.3 IMPLEMENTATION of Diffusion Processes; 2.7 Looking into Images with the Structural Tensor; 2.7.1 Structural Tensor in Two-Dimensional Image Space; 2.7.2 Spatio-Temporal Structural Tensor; 2.7.3 Multichannel and Scale-Space Structural Tensor; 2.7.4 Extended Structural Tensor; 2.7.4.1 IMPLEMENTATION of the Linear and Nonlinear Structural Tensor"]
[{"$nulls":4},"2.8 Object Representation with Tensor of Inertia and Moments2.8.1 "]
[{"$nulls":4},"IMPLEMENTATION of Moments and their Invariants; 2.9 Eigendecomposition and Representation of Tensors; 2.10 Tensor Invariants; 2.11 Geometry of Multiple Views: The Multifocal Tensor; 2.12 Multilinear Tensor Methods; 2.12.1 Basic Concepts of Multilinear Algebra; 2.12.1.1 Tensor Flattening; 2.12.1.2 IMPLEMENTATION Tensor Representation; 2.12.1.3 The k-mode Product of a Tensor and a Matrix; 2.12.1.4 Ranks of a Tensor; 2.12.1.5 IMPLEMENTATION of Basic Operations on Tensors; 2.12.2 Higher-Order Singular Value Decomposition (HOSVD)"]
[{"$nulls":4},"2.12.3 Computation of the HOSVD2.12.3.1 Implementation of the HOSVD Decomposition; 2.12.4 HOSVD Induced Bases; 2.12.5 Tensor Best Rank-1 Approximation; 2.12.6 Rank-1 Decomposition of Tensors; 2.12.7 Best Rank-(R1, R2, . . . , RP) Approximation; 2.12.8 Computation of the Best Rank-(R1, R2, . . . , RP) Approximations; 2.12.8.1 IMPLEMENTATION - Rank Tensor Decompositions; 2.12.8.2 CASE STUDY - Data Dimensionality Reduction; 2.12.9 Subspace Data Representation; 2.12.10 Nonnegative Matrix Factorization; 2.12.11 Computation of the Nonnegative Matrix Factorization"]
[{"$nulls":4},"2.12.12 Image Representation with NMF2.12.13 Implementation of the Nonnegative Matrix Factorization; 2.12.14 Nonnegative Tensor Factorization; 2.12.15 Multilinear Methods of Object Recognition; 2.13 Closure; 2.13.1 Chapter Summary; 2.13.2 Further Reading; 2.13.3 Problems and Exercises; References; 3 Classification Methods and Algorithms; 3.1 Abstract; 3.2 Classification Framework; 3.2.1 IMPLEMENTATION Computer Representation of Features; 3.3 Subspace Methods for Object Recognition; 3.3.1 Principal Component Analysis; 3.3.1.1 Computation of the PCA"]
[{"$nulls":4},"3.3.1.2 PCA for Multi-Channel Image Processing"]
[null,null,null,"Sommario/riassunto","Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications."]