Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It is complete in itself and includes background material. This makes it useful for a novice as well as for an expert. It reviews some of the existing probabilistic methods for image interpretation and presents some new results. Additionally, there is extensive bibliography covering references in varied areas.
For a researcher in this field, the material on synergistic integration of segmentation and interpretation modules and the Bayesian approach to image interpretation will be beneficial.
For a practicing engineer, the procedure for generating knowledge base, selecting initial temperature for the simulated annealing algorithm, and some implementation issues will be valuable.
New ideas introduced in the book include:
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It is complete in itself and includes background material. This makes it useful for a novice as well as for an expert. It reviews some of the existing probabilistic methods for image interpretation and presents some new results. Additionally, there is extensive bibliography covering references in varied areas. For a researcher in this field, the material on synergistic integration of segmentation and interpretation modules and the Bayesian approach to image interpretation will be beneficial. For a practicing engineer, the procedure for generating knowledge base, selecting initial temperature for the simulated annealing algorithm, and some implementation issues will be valuable. New ideas introduced in the book include: New approach to image interpretation using synergism between the segmentation and the interpretation modules. A new segmentation algorithm based on multiresolution analysis. Novel use of the Bayesian networks (causal networks) for image interpretation. Emphasis on making the interpretation approach less dependent on the knowledge base and hence more reliable by modeling the knowledge base in a probabilistic framework. Useful in both the academic and industrial research worlds, Bayesian Approach to Image Interpretation may also be used as a textbook for a semester course in computer vision or pattern recognition. 148 pp. Englisch. N° de réf. du vendeur 9780792373728
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It is complete in itself and includes background material. This makes it useful for a novice as well as for an expert. It reviews some of the existin. N° de réf. du vendeur 5970109
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Etat : New. Reviews probabilistic methods for image interpretation and presents the results. This book emphasizes on making the interpretation approach less dependent on the knowledge base and more reliable by modeling the knowledge base in a probabilistic framework. It is intended as a textbook for a semester course in computer vision or pattern recognition. Series: The Springer International Series in Engineering and Computer Science. Num Pages: 127 pages, biography. BIC Classification: UYQV; UYT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 234 x 166 x 14. Weight in Grams: 372. . 2001. Hardback. . . . . N° de réf. du vendeur V9780792373728
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Buch. Etat : Neu. Bayesian Approach to Image Interpretation | Sunil K. Kopparapu (u. a.) | Buch | xv | Englisch | 2001 | Springer | EAN 9780792373728 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 102593185
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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It is complete in itself and includes background material. This makes it useful for a novice as well as for an expert. It reviews some of the existing probabilistic methods for image interpretation and presents some new results. Additionally, there is extensive bibliography covering references in varied areas.For a researcher in this field, the material on synergistic integration of segmentation and interpretation modules and the Bayesian approach to image interpretation will be beneficial.For a practicing engineer, the procedure for generating knowledge base, selecting initial temperature for the simulated annealing algorithm, and some implementation issues will be valuable.New ideas introduced in the book include: New approach to image interpretation using synergism between the segmentation and the interpretation modules.A new segmentation algorithm based on multiresolution analysis.Novel use of the Bayesian networks (causal networks) for image interpretation.Emphasis on making the interpretation approach less dependent on the knowledge base and hence more reliable by modeling the knowledge base in a probabilistic framework.Useful in both the academic and industrial research worlds, Bayesian Approach to Image Interpretation may also be used as a textbook for a semester course in computer vision or pattern recognition.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 148 pp. Englisch. N° de réf. du vendeur 9780792373728
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