We present a neural system that recognizes faces under strong variations in pose and illumination. The generalization is learnt completely on the basis of examples of a subset of p...
The design of robust classifiers, which can contend with the noisy and outlier ridden datasets typical of computer vision, is studied. It is argued that such robustness requires l...
Realtime detection and localization of a road from an aerial image is an emerging research area that can be applied to vision-based navigation of unmanned air vehicles. Existing r...
We present a novel ``dynamic learning'' approach for an intelligent image database system to automatically improve object segmentation and labeling without user interven...
We develop an object classification method that can learn a novel class from a single training example. In this method, experience with already learned classes is used to facilita...