Title :
Using Bayesian neural networks to classify segmented images
Author :
Vivarelli, Francesco ; Williams, Christopher K I
Author_Institution :
Neural Comput. Res. Group, Aston Univ., Birmingham, UK
Abstract :
We present results that compare the performance of neural networks trained with two Bayesian methods, (i) the evidence framework of D.J.C. MacKay (1992) and (ii) a Markov chain Monte Carlo method due to R.M. 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
Keywords :
neural nets; Bayesian neural networks; Markov chain Monte Carlo method; automatic relevance determination method; evidence framework; input feature selection; performance; segmented images classification;
Conference_Titel :
Artificial Neural Networks, Fifth International Conference on (Conf. Publ. No. 440)
Conference_Location :
Cambridge
Print_ISBN :
0-85296-690-3
DOI :
10.1049/cp:19970738
