This paper proposes and develops a new graph-based semi-supervised learning method. Different from previous graph-based methods that are based on discriminative models, our method...
In this paper we propose a method for continuous learning of simple visual concepts. The method continuously associates words describing observed scenes with automatically extracte...
—A probabilistic formulation for semantic image annotation and retrieval is proposed. Annotation and retrieval are posed as classification problems where each class is defined as...
Gustavo Carneiro, Antoni B. Chan, Pedro J. Moreno,...
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...
The design of an optimal Bayesian classifier for multiple features is dependent on the estimation of multidimensional joint probability density functions and therefore requires a ...