Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, “pepper and salt” appears and classification results will be effected when the pixelwise classification algorithms are applied to highre...

Sparse coding has been popularly used as an effective data representation method in various applications, such as computer vision, medical imaging and bioinformatics, etc. However, the conventional sparse coding algorithms and its manifold regularized variants (graph sparse coding and Laplacian sparse coding), learn the codebook and codes in a unsupervised manner and neglect the class informati...

As one of the most visible applications in computer vision communication, face recognition (FR) has become significant role in the community. In the past decade, researchers have been devoting themselves to addressing the various problems emerging in practical FR applications in uncontrolled or less controlled environment. In many practical applications of FR (e.g., law enforcement, e-passport,...

The concept of virtual engineering (VEng) can be understood as a generalization of ”multi–disciplinary problem solving”, an ever more used term in scientific computing. An abstract space consisting of the physical, the geometrical, and the cost function directions, called CGP, is introduced. The VEng problem can be seen as a complex manifold embedded in this space. Common standard data formats,...

It is of great importance to classify the gene expression data into different classes. In this paper, followed the assumption that the gene expression data of tumor may be sampled from the data with a probability distribution on a sub-manifold of ambient space, an efficient feature extraction method named as Constrained Maximum Variance Mapping (CMVM), is presented for tumor classification. The...

We examine the stabilization of the two typical moduli, the length ρ of the eleventh segment and the volume V of the internal six manifold, in compactified heterotic M -theory. It is shown that, under certain conditions, the phenomenologically favored vacuum expectation values of ρ and V can be obtained by the combined effects of multi-gaugino condensations on the hidden wall and the membrane i...

Recently, multi-view representation learning has become a rapidly growing direction in machine learning and data mining areas. This paper first reviews the root methods and theories on multi-view representation learning, especially on canonical correlation analysis (CCA) and its several extensions. And then we investigate the advancement of multi-view representation learning that ranges from sh...

We present a new surface representation scheme based on a manifold structure and displacement functions. Given a geometric model represented as a point cloud, we construct a domain manifold which is a smooth surface blended from simple local patches. The original points are then projected on to the local patches and their displacements are adjusted so that the final displaced surface approximat...