Similarity based pattern analysis recognition (28 resultados)

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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a 'kernel tailoring' approach and a strategy for learning similarities directly from training data; describes various methods for 'structure-preserving' embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imagingapplications.…

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a 'kernel tailoring' approach and a strategy for learning similarities directly from training data; describes various methods for 'structure-preserving' embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imagingapplications.…

Condición: New. pp. 308.

Taschenbuch. Condición: Neu. Similarity-Based Pattern Analysis and Recognition | Marcello Pelillo | Taschenbuch | Advances in Computer Vision and Pattern Recognition | xiv | Englisch | 2016 | Springer | EAN 9781447169505 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Condición: Sehr gut. Zustand: Sehr gut | Seiten: 308 | Sprache: Englisch | Produktart: Bücher | This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a ¿kernel tailoring¿ approach and a strategy for learning similarities directly from training data; describes various methods for ¿structure-preserving¿ embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imagingapplications.…

Condición: New. pp. 291.

Condición: new. Questo è un articolo print on demand.

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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a 'kernel tailoring' approach and a strategy for learning similarities directly from training data; describes various methods for 'structure-preserving' embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imaging applications. 308 pp. Englisch.…

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a 'kernel tailoring' approach and a strategy for learning similarities directly from training data; describes various methods for 'structure-preserving' embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imaging applications. 308 pp. Englisch.…

Kartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a coherent overview of the emerging field of non-Euclidean similarity learningPresents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world.…

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a coherent overview of the emerging field of non-Euclidean similarity learningPresents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world.…

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a ¿kernel tailoring¿ approach and a strategy for learning similarities directly from training data; describes various methods for ¿structure-preserving¿ embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imagingapplications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 308 pp. Englisch.…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely theoretical challenges to practical, real-world applications. The coverage includes both supervised and unsupervised learning paradigms, as well as generative and discriminative models. Topics and features: explores the origination and causes of non-Euclidean (dis)similarity measures, and how they influence the performance of traditional classification algorithms; reviews similarity measures for non-vectorial data, considering both a ¿kernel tailoring¿ approach and a strategy for learning similarities directly from training data; describes various methods for ¿structure-preserving¿ embeddings of structured data; formulates classical pattern recognition problems from a purely game-theoretic perspective; examines two large-scale biomedical imagingapplications.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 308 pp. Englisch.…

Condición: New. Print on Demand pp. 308 65 Illus. (46 Col.).

Condición: New. PRINT ON DEMAND pp. 308.

Condición: New. Print on Demand pp. 291.

Condición: New. PRINT ON DEMAND pp. 291.