ISBN: 9783319272511 - structural pattern recognition with graph edit distance: approximation algorithms and applications (advances in computer vision and pattern recognition) (12 resultados)

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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). The book also provides a detailed review of a diverse selection of novel methods related to GED, and concludes by suggesting possible avenues for future research. Topics and features: formally introduces the concept of GED, and highlights the basic properties of this graph matching paradigm; describes a reformulation of GED to a quadratic assignment problem; illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem; reviews strategies for reducing both the overestimation of the true edit distance and the matching time in the approximation framework; examines the improvement demonstrated by the described algorithmic framework with respect to the distance accuracy and the matching time; includes appendices listing the datasets employed for the experimental evaluations discussedin the book.…

Condición: New. pp. 152.

Hardcover. Condición: Brand New. 174 pages. 9.25x6.25x0.50 inches. In Stock.

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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). The book also provides a detailed review of a diverse selection of novel methods related to GED, and concludes by suggesting possible avenues for future research. Topics and features: formally introduces the concept of GED, and highlights the basic properties of this graph matching paradigm; describes a reformulation of GED to a quadratic assignment problem; illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem; reviews strategies for reducing both the overestimation of the true edit distance and the matching time in the approximation framework; examines the improvement demonstrated by the described algorithmic framework with respect to the distance accuracy and the matching time; includes appendices listing the datasets employed for the experimental evaluations discussed in the book. 172 pp. Englisch.…

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a thorough introduction to the concept of graph edit distance (GED) Describes a selection of diverse GED algorithms with step-by-step examples Presents a unique overview of recent pattern recognition applications based on GED.…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This unique text/reference presents a thorough introduction to the field of structural pattern recognition, with a particular focus on graph edit distance (GED). The book also provides a detailed review of a diverse selection of novel methods related to GED, and concludes by suggesting possible avenues for future research. Topics and features: formally introduces the concept of GED, and highlights the basic properties of this graph matching paradigm; describes a reformulation of GED to a quadratic assignment problem; illustrates how the quadratic assignment problem of GED can be reduced to a linear sum assignment problem; reviews strategies for reducing both the overestimation of the true edit distance and the matching time in the approximation framework; examines the improvement demonstrated by the described algorithmic framework with respect to the distance accuracy and the matching time; includes appendices listing the datasets employed for the experimental evaluations discussed in the book.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 172 pp. Englisch.…

Condición: New. Print on Demand pp. 152.

Condición: New. PRINT ON DEMAND pp. 152.