In many complex machine learning applications there is a need to learn multiple interdependent output variables, where knowledge of these interdependencies can be exploited to impr...
In this paper, we develop a new approach for texture classification independent of affine transforms. Based on spectral representation of texture images under affine transform, an...
In the paper a new measure of distance between events/observations in the pattern space is proposed and experimentally evaluated with the use of k-NN classifier in the context of b...
: A new supervised learning procedure for training RBF networks is proposed. It uses a pair of parallel running Kalman filters to sequentially update both the output weights and th...
In schema integration, schematic discrepancies occur when data in one database correspond to metadata in another. We explicitly declare the context that is the meta information re...