In this paper, we develop data driven registration algorithms, relying on robust pixel similarity metrics, that enable an accurate (subpixel) rigid registration of dissimilar singl...
Traditionally, machine learning algorithms have been evaluated in applications where assumptions can be reliably made about class priors and/or misclassification costs. In this pa...
In this paper, we address issues in segmentation of remotely sensed LIDAR (LIght Detection And Ranging) data. The LIDAR data, which were captured by airborne laser scanner, contai...
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
This paper describes an evolutionary clustering algorithm, which can partition a given dataset automatically into the optimal number of groups through one shot of optimization. The...