Please use this identifier to cite or link to this item:
- Human face verification based on multidimensional Polynomial Powers of Sigmoid (PPS)
- Universidade Estadual Paulista (UNESP)
- In this paper, we described how a multidimensional wavelet neural networks based on Polynomial Powers of Sigmoid (PPS) can be constructed, trained and applied in image processing tasks. In this sense, a novel and uniform framework for face verification is presented. The framework is based on a family of PPS wavelets,generated from linear combination of the sigmoid functions, and can be considered appearance based in that features are extracted from the face image. The feature vectors are then subjected to subspace projection of PPS-wavelet. The design of PPS-wavelet neural networks is also discussed, which is seldom reported in the literature. The Stirling Universitys face database were used to generate the results. Our method has achieved 92 % of correct detection and 5 % of false detection rate on the database.
- Healthinf 2008: Proceedings of The First International Conference on Health Informatics, Vol 2. Setubal: Insticc-inst Syst Technologies Information Control & Communication, p. 99-106, 2008.
- Insticc-inst Syst Technologies Information Control & Communication
- artificial neural network
- human face verification
- Polynomial Powers of Sigmoid (PPS)
- wavelets functions
- PPS-wavelet neural networks
- activation functions
- feedforward networks
- Acesso restrito
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.