Clustering within Integrate-and-Fire Neurons for Image Segmentation

Authors:
Phill Rowcliffe;Jianfeng Feng;Hilary Buxton
Affiliations:
-;-;-
Venue:
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Year:
2002

Citing 3
Cited 1

Self-Organization of Pulse-Coupled Oscillators with Application to Clustering

IEEE Transactions on Pattern Analysis and Machine Intelligence
Reduction of the hodgkin-huxley equations to a single-variable threshold model

Neural Computation
Weight adaptation and oscillatory correlation for image segmentation

IEEE Transactions on Neural Networks

Segmentation and Edge Detection Based on Spiking Neural Network Model

Neural Processing Letters

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Abstract

An algorithm is developed to produce self-organisation of a purely excitatory network of Integrate-and-Fire (IF) neurons, receiving input from a visual scene. The work expands on a clustering algorithm, previously developed for Biological Oscillators, which self-organises similar oscillators into groups and then clusters these groups together. Pixels from an image are used as scalar inputs for the network, and segmented as the oscillating neurons are clustered into synchronised groups.