An endmember detection algorithm for hyperspectral imagery using the Dirichlet process to determine the number of endmembers in a hyperspectral image is described. This algorithm ...
A new graph algorithm for multiscale segmentation of threedimensional medical data sets is presented. It is a threedimensional generalisation of an existing two-dimensional Mumfor...
We introduce an algorithm that learns gradients from samples in the supervised learning framework. An error analysis is given for the convergence of the gradient estimated by the ...
This paper describes the selection and automation of a method for estimating how many replications should be run to achieve a required accuracy in the output. The motivation is to...
Background: Supervised learning for classification of cancer employs a set of design examples to learn how to discriminate between tumors. In practice it is crucial to confirm tha...