We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...
In this paper, we present a new approach for image labeling based on the recently introduced graph-shifts algorithm. Graph-shifts is an energy minimization algorithm that does lab...
The deconvolution of blurred and noisy satellite images is an ill-posed inverse problem, which can be regularized within a Bayesian context by using an a priori model of the recon...
This paper introduces a faceted model of image semantics which attempts to express the richness of semantic content interpretable within an image. Using a large image data-set fro...
Jonathon S. Hare, Paul H. Lewis, Peter G. B. Enser...
During the past years, the development of microarray technology has been remarkable, and it is becoming a daily tool in many genomic research laboratories. The widespread adoption...