Using models in different contexts poses major integration challenges, ranging from technical to conceptual levels. Independently of each other developed model components cannot b...
Probabilistic models of languages are fundamental to understand and learn the profile of the subjacent code in order to estimate its entropy, enabling the verification and predicti...
The wavelet transform has been used for feature extraction in many applications of pattern recognition. However, in general the learning algorithms are not designed taking into acc...
Over the last several years, a new probabilistic representation for 3-d volumetric modeling has been developed. The main purpose of the model is to detect deviations from the norm...
One of the main objectives of developing component-based software systems is to enable efficient building of systems through the integration of components. All component models def...