Compressive sensing accurately reconstructs a signal that is sparse in some basis from measurements, generally consisting of the signal’s inner products with Gaussian random vec...
Abstract. Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the sc...
Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...
In this work we tackle the open problem of self-join size (SJS) estimation in a large-scale Distributed Data System, where tuples of a relation are distributed over data nodes whic...
This paper describes a local ensemble kernel learning technique to recognize/classify objects from a large number of diverse categories. Due to the possibly large intraclass featu...