Development and spatial structure of cortical feature maps: a model study
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
Neural computation and self-organizing maps: an introduction
Neural computation and self-organizing maps: an introduction
Parametrized SOMs for Object Recognition and Pose Estimation
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Analysis of neighborhood interaction in Kohonen neural networks
IPPS '91 Proceedings of the Fifth International Parallel Processing Symposium
SOM of SOMs: self-organizing map which maps a group of self-organizing maps
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
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One of important subjects for mobile robots is the vision based decision making system, where the color constancy is big problem for robots which use color property to recognize environments. We have been working on color constancy vision algorithms using bio-inspired information processing as creatures can recognize color and shape of objects even if there exits a large change of light conditions in outdoor environments. In this paper, we evaluate the performances of color recognition using bio-inspired processing algorithms such as Self-Organizing Map (SOM), modular network SOM (mnSOM) and Neural Gas (NG). The experimental results in various light conditions are discussed.