Title :
Weightless neural nets for face recognition: a comparison
Author :
Lauria, S. ; Mitchell, R.J.
Author_Institution :
Dept. of Cybern., Reading Univ., UK
fDate :
31 Aug-2 Sep 1998
Abstract :
This 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
Keywords :
biometrics (access control); face recognition; generalisation (artificial intelligence); image matching; learning (artificial intelligence); neural nets; access control; expression variability; face recognition; generalisation; image matching; learning algorithm; weightless neural networks; Computational modeling; Computer simulation; Cybernetics; Face recognition; Hidden Markov models; Neural networks; Neurons; Pattern recognition; Read-write memory; Testing;
Conference_Titel :
Neural Networks for Signal Processing VIII, 1998. Proceedings of the 1998 IEEE Signal Processing Society Workshop
Conference_Location :
Cambridge
Print_ISBN :
0-7803-5060-X
DOI :
10.1109/NNSP.1998.710685