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Similarity-Based Pattern Recognition [electronic resource] :First International Workshop, SIMBAD 2011, Venice, Italy, September 28-30, 2011. Proceedings /

Contributor(s): Pelillo, Marcello [editor.] | Hancock, Edwin R [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 7005Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011.Description: XIII, 333 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642244711.Subject(s): Computer science | Algorithms | Database management | Artificial intelligence | Image processing | Pattern recognition | Computer Science | Pattern Recognition | Image Processing and Computer Vision | Artificial Intelligence (incl. Robotics) | Database Management | Algorithm Analysis and Problem Complexity | Information Systems Applications (incl. Internet)Online resources: Click here to access online In: Springer eBooksSummary: 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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