Using Bayesian neural networks to classify segmented images

Abstract

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.

Publication DOI: https://doi.org/10.1049/cp:19970738
Divisions: Aston University (General)
Uncontrolled Keywords: neural networks,Automatic Relevance Determination,feature selection
ISBN: 0852966903
Full Text Link:
Related URLs: http://ieeexplo ... &isnumber=13303 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Chapter
Published Date: 1997-07-09
Authors: Vivarelli, Francesco
Williams, Christopher K. I.

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