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Baum-Eagon inequality in probabilistic labeling problems

Author

Listed:
  • Crescenzio Gallo

    (Università di Foggia-Dipartimento di Scienze Economiche, Matematiche e Statistiche)

  • Giancarlo de Stasio

    (Università di Foggia)

Abstract

This work illustrates an approach to the study of labeling, aka 'object classification'. This kind of parallel computing problem well suites to AI applications (pattern recognition, edge detection, etc.) Our target consists in simplifying an overly computationally costly algorithm proposed by Faugeras and Berthod; using Baum-Eagon theorem, we obtained a reduced algorithm which produces results comparable with other more complex approaches.

Suggested Citation

  • Crescenzio Gallo & Giancarlo de Stasio, 2005. "Baum-Eagon inequality in probabilistic labeling problems," Experimental 0509003, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpex:0509003
    Note: Type of Document - pdf; pages: 12
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    More about this item

    Keywords

    labeling; artificial intelligence; edge detection; probabilistic algorithms; pixel classification;
    All these keywords.

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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