Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
— For a robot to understand a scene, we have to infer and extract meaningful information from vision sensor data. Since scene understanding consists in recognizing several visual...
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Nowadays, large distributed databases are commonplace. Client applications increasingly rely on accessing objects from multiple remote hosts. The Internet itself is a huge network ...
Interpersonal interaction plays an important role in organizational dynamics, and understanding these interaction networks is a key issue for any organization, since these can be ...