Face recognition using radial basis function (RBF) neural networks
Meng Joo Er, Shiqian Wu, Juwei Lu · 2003
This paper presents some new results on face recognition using Radial Basis Function (RBF) Neural Networks. First, face features are extracted by discriminant eigenfeatures. Then, a general approach, which determines the initial structure and parameters of RBF neural networks, is presented. A hybrid learning algorithm is used to dramatically decrease the dimension of the search space in the gradient method, which is crucial on optimization of high-dimension problem. Experimental results conducted on the ORL database image of Cambridge University show that the error rate is 1.5% which is a tremendous improvement over the best existing result of 3.83%.