Using Bayesian neural networks to classify segmented images

Francesco Vivarelli, Christopher K. I. Williams

    Research output: Chapter in Book/Published conference outputChapter


    We present results that compare the performance of neural networks trained with two Bayesian methods, (i) the Evidence Framework of MacKay (1992) and (ii) a Markov Chain Monte Carlo method due to Neal (1996) on a task of classifying segmented outdoor images. We also investigate the use of the Automatic Relevance Determination method for input feature selection.
    Original languageEnglish
    Title of host publicationFifth International Conference on Artificial Neural Networks
    Place of PublicationCambridge, UK
    PublisherAston University
    Number of pages6
    ISBN (Print)0852966903
    Publication statusPublished - 9 Jul 1997


    • neural networks
    • Automatic Relevance Determination
    • feature selection


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