We discuss the use of normal distribution theory as a tool to model the convergence characteristics of di erent GA selection schemes. The models predict the proportion of optimal a...
We apply robust Bayesian decision theory to improve both generative and discriminative learners under bias in class proportions in labeled training data, when the true class propo...
The Gaussian kernel density estimator is known to have substantial problems for bounded random variables with high density at the boundaries. For i.i.d. data several solutions hav...
In order to develop a high-level description of events unfolding in a typical surveillance scenario, each successfully tracked event must be classified into type and behaviour. I...
This paper presents a Bayesian Network model for ContentBased Image Retrieval (CBIR). In the explanation and test of this work, only two images features (semantic evidences) are i...
Paulo S. Rodrigues, Gilson A. Giraldi, Ade A. Arau...