Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
In this paper, we present an effective algorithm to construct a 3D shape atlas for the left ventricle of heart from cardiac Magnetic Resonance Image data. We derive a framework tha...
— The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem...
Dacheng Tao, Xuelong Li, Xindong Wu, Stephen J. Ma...
Clustering is to identify densely populated subgroups in data, while correlation analysis is to find the dependency between the attributes of the data set. In this paper, we combin...
We present in this paper a novel approach for shape description based on kernel principal component analysis (KPCA). The strength of this method resides in the similarity (rotatio...