Similarity-Based Pattern Recognition [electronic resource] : First International Workshop, SIMBAD 2011, Venice, Italy, September 28-30, 2011, Proceedings / edited by Marcello Pelillo, Edwin R. Hancock.
Contributor(s): Pelillo, Marcello [editor.]
| Hancock, Edwin R [editor.] | SpringerLink (Online service).
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BookSeries: Image Processing, Computer Vision, Pattern Recognition, and Graphics: 7005Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011Edition: 1st ed. 2011.Description: XIII, 333 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642244711.Subject(s): Pattern recognition systems | Computer vision | Artificial intelligence | Database management | Algorithms | Application software | Automated Pattern Recognition | Computer Vision | Artificial Intelligence | Database Management | Algorithms | Computer and Information Systems ApplicationsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.4 Online resources: Click here to access online
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Springer Nature eBookSummary: This book constitutes the proceedings of the First International Workshop on Similarity Based Pattern Recognition, SIMBAD 2011, held in Venice, Italy, in September 2011. The 16 full papers and 7 poster papers presented were carefully reviewed and selected from 35 submissions. The contributions are organized in topical sections on dissimilarity characterization and analysis; generative models of similarity data; graph-based and relational models; clustering and dissimilarity data; applications; spectral methods and embedding.
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This book constitutes the proceedings of the First International Workshop on Similarity Based Pattern Recognition, SIMBAD 2011, held in Venice, Italy, in September 2011. The 16 full papers and 7 poster papers presented were carefully reviewed and selected from 35 submissions. The contributions are organized in topical sections on dissimilarity characterization and analysis; generative models of similarity data; graph-based and relational models; clustering and dissimilarity data; applications; spectral methods and embedding.
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