Using Bayesian neural networks to classify segmented images
| Data(s) |
09/07/1997
|
|---|---|
| Resumo |
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. |
| Formato |
application/pdf |
| Identificador |
http://eprints.aston.ac.uk/1193/1/Artificial_Neural_Networks.pdf 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. |
| Publicador |
Aston University |
| Relação |
http://eprints.aston.ac.uk/1193/ |
| Tipo |
Book Section NonPeerReviewed |
