When using machine learning for in silico modeling, the goal is normally to obtain highly accurate predictive models. Often, however, models should also bring insights into intere...
: This work presents a new hybrid neuro-fuzzy model for automatic learning of actions taken by agents. The main objective of this new model is to provide an agent with intelligence...
Karla Figueiredo, Marley B. R. Vellasco, Marco Aur...
The design of appropriate communication architectures for complex Systems-on-Chip (SoC) is a challenging task. One promising alternative to solve these problems are Networks-on-Ch...
Holger Blume, Thorsten von Sydow, Daniel Becker, T...
Kernel machines have recently been considered as a promising solution for implicit surface modelling. A key challenge of machine learning solutions is how to fit implicit shape mo...
Statistical modeling for content based retrieval is examined in the context of recent TREC Video benchmark exercise. The TREC Video exercise can be viewed as a test bed for evalua...
Milind R. Naphade, Sankar Basu, John R. Smith, Chi...