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...
The advent of advanced graphics technologies and improved hardware has enabled the generation of highly complex models with huge number of triangles. Point-based representations a...
Kedarnath Thangudu, Lakshmi Gade, Jag Mohan Singh,...
Statistical models of deformations (SMD) capture the variability of deformations of a group of sample images, and they are often used to constrain deformable registration, thereby...