Supervised methods for learning an embedding aim to map high-dimensional images to a space in which perceptually similar observations have high measurable similarity. Most approac...
Graham Taylor, Ian Spiro, Rob Fergus, Christoph Br...
This paper outlines a series of experiments looking at the annotation and subsequent analysis of skills-based learning and teaching in the domain of Nursing. The experiments used ...
Mark J. Weal, Danius T. Michaelides, Kevin R. Page...
Surveillance systems that operate continuously generate large volumes of data. One such system is described here, continuously tracking and storing observations taken from multiple...
Abstract. We investigate the use of parameterized state machine models to drive integration testing, in the case where the models of components are not available beforehand. Theref...
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how their sparse recovery fails whenever we can only measure a convolved observation...