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.
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Rowcliffe, P., Feng, J., Buxton, H. (2002). Clustering within Integrate-and-Fire Neurons for Image Segmentation. In: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_12
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DOI: https://doi.org/10.1007/3-540-46084-5_12
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