Self-organizing maps and adaptive filters
Models of neural networks
Asymptotic level density for a class of vector quantization processes
IEEE Transactions on Neural Networks
Unsupervised learning and self-organization in networks of spiking neurons
Self-Organizing neural networks
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Topographic Independent Component Analysis
Neural Computation
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The process of visual feature abstraction begins in the retina and proceeds at each subsequent level of visual processing. In this article we review recent advance in the functional mapping of striate cortex in primates and explore ways in which the observed maps may facilitate tasks of scene segmentation in subsequent cortical areas. In so doing we also explore the possible origins of these maps from simple self-organizing processes, based on Hebbian learning, and find that within this framework, the observed maps can be interpreted as the neighborhood preserving projections of five-dimensional feature space onto the two available dimensions of striate cortex.