As basic research, it has also received increasing attention from people that the “curse of
dimensionality” will lead to increase the cost of data storage and computing; it also …

One of the major challenges encountered by current face recognition techniques lies in the
difficulties of handling varying poses, ie, recognition of faces in arbitrary in-depth rotations …

Making recognition more reliable under uncontrolled lighting conditions is one of the most
important challenges for practical face recognition systems. We tackle this by combining the …

Forward-looking sonar is one of the essential imaging equipment used in exploring
underwater targets. However, it is always challenging to detect targets from sonar images …

We introduce the use of describable visual attributes for face verification and image search.
Describable visual attributes are labels that can be given to an image to describe its …

Local binary patterns (LBP) are one of the most important image representations. However,
LBPs have not been as successful as other methods in palmprint recognition. Originally, the …

This paper proposes a new unsupervised spectral feature selection method to preserve both
the local and global structure of the features as well as the samples. Specifically, our method …

Recently, manifold learning has been widely exploited in pattern recognition, data analysis,
and machine learning. This paper presents a novel framework, called Riemannian manifold …

We are currently witnessing an important paradigm shift in information system construction,
namely the move from object and component technology to model technology. The object …

Pattern recognition has been employed in a myriad of industrial, commercial and academic
applications. Many techniques have been devised to tackle such a diversity of applications …