Bayesian Approach to Image Interpretation: 616 (The Springer International Series in Engineering and Computer Science) - Tapa blanda

Kopparapu, Sunil K.; Desai, Uday B.

 
9781475774832: Bayesian Approach to Image Interpretation: 616 (The Springer International Series in Engineering and Computer Science)
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ISBN 10: 1475774834 ISBN 13: 9781475774832
Editorial: Springer, 2013

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Springer
Año de publicación
2013
Idioma
Inglés
ISBN 10 
1475774834
ISBN 13 
9781475774832
Encuadernación
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Número de páginas
148
Contacto del fabricante
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Alemania

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9781475774825: Bayesian Approach to Image Interpretation

Edición Destacada

ISBN 10:  1475774826 ISBN 13:  9781475774825
Editorial: Springer, 2013
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