Loopy belief propagation and probabilistic image processing

Kazuyuki Tanaka, Jun Ichi Inoue, D. M. Titterington

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Estimation of hyperparameters by maximization of the marginal likelihood in probabilistic image processing is investigated by using the cluster variation method. The algorithms are substantially equivalent to generalized loopy belief propagation.

Original languageEnglish
Title of host publication2003 IEEE 13th Workshop on Neural Networks for Signal Processing, NNSP 2003
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages329-338
Number of pages10
ISBN (Electronic)0780381777
DOIs
Publication statusPublished - 2003
Event13th IEEE Workshop on Neural Networks for Signal Processing, NNSP 2003 - Toulouse, France
Duration: 2003 Sep 172003 Sep 19

Publication series

NameNeural Networks for Signal Processing - Proceedings of the IEEE Workshop
Volume2003-January

Other

Other13th IEEE Workshop on Neural Networks for Signal Processing, NNSP 2003
CountryFrance
CityToulouse
Period03/9/1703/9/19

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Software
  • Computer Networks and Communications
  • Signal Processing

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