The paper describes the model, implementation and experimental evaluation of a distributed Kohonen Neural Network application (Kohonen Application). The aim of this research is to...
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
A system for automatically classifying the trajectory of a moving object in a scene as usual or suspicious is presented. The system uses an unsupervised neural network (Self Organi...
Kofi Appiah, Andrew Hunter, Tino Kluge, Philip Aik...
Real-time, static and dynamic hand gesture learning and recognition makes it possible to have computers recognize hand gestures naturally. This creates endless possibilities in the...
Todd C. Alexander, Hassan S. Ahmed, Georgios C. An...