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Bayesian Approach to Image Interpretation

Name: Bayesian Approach to Image Interpretation
Brand: Springer-Verlag New York Inc.
SKU: 9781475774832
Price: 826.09 RON
Availability: InStock

Autor: Sunil K. Kopparapu, Uday B. Desai

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Editura: Springer-Verlag New York Inc.

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Bayesian Approach to Image Interpretation will interest anyone working in image interpretation. It i...

Informații despre carte

Autor

Sunil K. Kopparapu, Uday B. Desai

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2013

Pagini

127

EAN

9781475774832

ISBN

1475774834

Enbook ID

02643891

Editura

Springer-Verlag New York Inc.

Greutate

237

Dimensiuni

155 x 235 x 9

Descriere completă

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.

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