In this paper we present the results of a comparative study of linear and kernel-based methods for face recognition. The methods used for dimensionality reduction are Principal Co...
Himaanshu Gupta, Amit K. Agrawal, Tarun Pruthi, Ch...
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...
Jie Wang, Konstantinos N. Plataniotis, Anastasios ...
Information Fusion of multi-modal Biometrics has attracted much attention in recent years. However, this paper focuses on the information fusion in single modals, that is, the fac...
Bo Cao, Peng Yang, Shiguang Shan, Wen Gao, Wenchao...
We describe an analog-VLSI neural network for face recognition based on subspace methods. The system uses a dimensionality-reduction network whose coefficients can be either progr...
Gonzalo Carvajal, Waldo Valenzuela, Miguel Figuero...
Linear Discriminant Analysis (LDA) is a well-known method for feature extraction and dimension reduction. It has been used widely in many applications such as face recognition. Re...
Tao Xiong, Jieping Ye, Qi Li, Ravi Janardan, Vladi...