Learning and neural networks

Learning and neural networks Intelligent systems need to learn in order to cope with changing environments or inaccurate a-priori knowledge. Learning from data is studied in the context of autonomous systems. Originally we focussed on neural networks, now we look more general to probabilistic methods. We have the following projects:

Neurocontrol and reinforcement learning
Active map building and sensoric representation (RWCP project)
Probabilistic models for distributed surveillance systems NEW! Short project decription (Full description in Dutch)
Face detection with neural networks
Aircraft recognition from radar profiles

Finished projects:

Robot arm control
Sensor data fusion
Function approximation

Teaching:

Introduction Neural Networks and Statistical Pattern Recognition
Capita Neuro Informatics

Links to neural pages

pages maintained by: Ben Kröse