Vivarelli, Francesco and Williams, Christopher K. I. (1997). Using Bayesian neural networks to classify segmented images. IN: Fifth International Conference on Artificial Neural Networks. Cambridge, UK: Aston University.
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 |
| Last Modified: | 01 Nov 2024 08:43 |
| Date Deposited: | 11 Mar 2019 16:36 |
| 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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