Cost-sensitive face recognition is a challenging problem in pattern recognition. Due to the
high-dimensional face features, cost-sensitive face recognition usually conducts feature …

Abstract Hyper-Spectral Image (HSI) classification is an important task because of its wide
range of applications. With the remarkable success from the Convolutional Neural Network …

In current graph embedding methods, low dimensional projections are obtained by
preserving either global geometrical structure of data or local geometrical structure of data …

For a broad range of applications, hyperspectral image (HSI) classification is a hot topic in
remote sensing, and convolutional neural network (CNN)-based methods are drawing …

Gesture recognition has become a research hotspot in the fields of human–computer
interaction, sign language recognition, rehabilitation training, sports medicine, etc. The …

L1-norm discriminant analysis has been proposed to enhance the robustness of classical
LDA in the presence of outliers. This paper develops L1-norm discriminant analysis by …

Intuitively, all facial images of a person are located on or near a manifold in the high-
dimensional image space, and the process of face recognition can be regarded as the …

Dimensionality reduction techniques are powerful tools for face recognition, because they
obtain important information from a dataset. Several dimensionality reduction methods …

Due to the spectral complexity and high dimensionality of hyperspectral images (HSIs), the
processing of HSIs is susceptible to the curse of dimensionality. In addition, the classification …

Transfer learning (TL) method has captured an attractive presence because it facilitates the
learning ability in the target domain by acquiring knowledge from well-established source …