Date: 29 Sep 2009

Object recognition in industrial environments using support vector machines and artificial neural networks

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This paper presents a comparison between Artificial Neural Networks and Support Vector Machines in the application of classifying automotive wheels in an industrial environment. Performance of these two approaches over a range of classifier parameters on a data set pre-processed in multiple ways has been evaluated and the results analysed. Results indicate that the best performance is obtained using a support vector machine approach incorporating a linear kernel.