The new model reduces the impact of local spectral and temporal variability by estimating a finite set of spectral and temporal warping factors which are applied to speech at the f...
Antonio Miguel, Eduardo Lleida, Richard Rose, Luis...
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
Linear Discriminant Analysis (LDA) has been a popular method for feature extracting and face recognition. As a supervised method, it requires manually labeled samples for training...
Background: Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) ...
Bin Liu, Xiaolong Wang, Lei Lin, Qiwen Dong, Xuan ...
This paper presents a method to quantitatively evaluate
information contributions of individual bottom-up and topdown
computing processes in object recognition. Our objective
is...