Speaker independent feature extraction is a critical problem in speech recognition. Oriented principal component analysis (OPCA) is a potential solution that can find a subspace r...
Current technology trends have led to the growing impact of both inter-die and intra-die process variations on circuit performance. While it is imperative to model parameter varia...
Face recognition under unconstrained illuminations (FR/I) received extensive study because of the existence of illumination subspace. [2] presented a study on the comparison betwe...
We study the use of kernel subspace methods for learning low-dimensional representations for classification. We propose a kernel pooled local discriminant subspace method and com...
This paper introduces a framework that employs the Fisher linear discriminant model (FLDM) and classifier (FLDC) on integrated facial appearance and facial expression features. T...
Pohsiang Tsai, Tich Phuoc Tran, Tom Hintz, Tony Ja...