We present a novel iterative nonlinear filtering framework, termed multilateral filtering, based on the idea of generic local similarity. A set of local features is computed for e...
We propose a new local learning scheme that is based on the principle of decisiveness: the learned classifier is expected to exhibit large variability in the direction of the test ...
Traditional background modeling and subtraction methods have a strong assumption that the scenes are of static structures with limited perturbation. These methods will perform poo...
— When using appearance-based recognition for self-localization of mobile robots, the images obtained during the exploration of the environment need to be efficiently stored in t...
Feature Filtering is an approach that is widely used for dimensionality reduction in text categorization. In this approach feature scoring methods are used to evaluate features le...
Nayer M. Wanas, Dina A. Said, Nevin M. Darwish, Na...