Given discrete event data, we wish to produce a probability density that can model the relative probability of events occurring in a spatial region. Common methods of density esti...
Laura M. Smith, Matthew S. Keegan, Todd Wittman, G...
We present an introspection/reflection framework for SystemC which extracts design-relevant structure information and transaction data under any LRM-2.1 compliant simulation kern...
One of the main problems in the radiosity method is how to discretise a scene into mesh elements that allow us to accurately represent illumination. In this paper we present a new ...
Previous research applying kernel methods such as support vector machines (SVMs) to hyperspectral image classification has achieved performance competitive with the best available ...
Baofeng Guo, Steve R. Gunn, Robert I. Damper, Jame...
Segmentation involves separating an object from the background. In this work, we propose a novel segmentation method combining image information with prior shape knowledge, within...
Samuel Dambreville, Yogesh Rathi, Allen Tannenbaum