Authors:
Philipp Wolfrum
1
;
Jörg Lücke
2
and
Christoph von der Malsburg
1
Affiliations:
1
Frankfurt Institute for Advanced Studies, JWG University, Germany
;
2
Gatsby Unit, UCL, United Kingdom
Keyword(s):
Face recogntion, Neural model, Recurrent network, Generative model, Dynamic links, Cortical column, Self-organization.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
We describe a neural network for invariant object recognition. The network is generative in the sense that it explicitly represents both the recognized object and the extrinsic properties to which it is invariant (especially object position). The model is biologically plausible, being formulated as a neuronal system composed of cortical columns. At the same time it has competitive face recognition performance.