Weightless neural nets for face recognition: a comparisonLauria, S. and Mitchell, R. J. (1998) Weightless neural nets for face recognition: a comparison. In: Neural networks for signal processing VIII. Proceedings of the 1998 IEEE signal processing society workshop. IEEE, pp. 539-546. ISBN 078035060X Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1109/NNSP.1998.710685 Abstract/SummaryThis paper considers the application of weightless neural networks (WNNs) to the problem of face recognition and compares the results with those provided using a more complicated multiple neural network approach. WNNs have significant advantages over the more common forms of neural networks, in particular in term of speed of operation and learning. A major difficulty when applying neural networks to face recognition problems is the high degree of variability in expression, pose and facial details: the generalisation properties of a WNN can be crucial. In the light of this problem a software simulator of a WNN has been built and the results of some initial tests are presented and compared with other techniques
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