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Abstract: This thesis investigates feedforward neural networks in the context of classification tasks with respect to the detection of patterns that do not belong to the same categories of patterns used to train the network. This refers to the problem of the detection and/or rejection of spurious or novel patterns. In particular, the multilayer perceptron network (MLP) trained with the backpropagation algorithm is examined in this respect and different strategies for improving its performance in the... (Update)
Context of citations to this paper: More
...of this mechanism is shown in the classification of handwritten characters. 1 Introduction The detection of spurious or novel [5, 7] patterns is an issue of great practical importance to many applications of neural networks. For example, in a factory control process...
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BibTeX entry: (Update)
Vasconcelos, G.C. (1995). `An investigation of feedforward neural networks with respect to the detection of spurious patterns'. PhD Thesis, Electronic Engineering Labs, University of Kent, U.K. http://citeseer.ist.psu.edu/vasconcelos95investigation.html More
@misc{ vasconcelos95investigation,
author = "G. Vasconcelos",
title = "An investigation of feedforward neural networks with respect to the detection
of spurious patterns",
text = "Vasconcelos, G.C. (1995). `An investigation of feedforward neural networks
with respect to the detection of spurious patterns'. PhD Thesis, Electronic
Engineering Labs, University of Kent, U.K.",
year = "1995",
url = "citeseer.ist.psu.edu/vasconcelos95investigation.html" }
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