Performance Comparison of Computational Retina Models

J.C. Martins and L.A. Sousa (Portugal)


Retina models. Computational models. Visual image pro cessing. Error measures.


A comparative study of bio-inspired computational retina models, representative of two distinct model classes, is pre sented in this paper. One model belongs to the so called class of pseudo-deterministic models, where a given light stimulus always produces the same response, while the other analyzed model belongs to the stochastic class and mimics the random behavior of the retina response. Both the firing rate and spike train metrics are used to evaluate and compare both models. Experimental results, obtained with real data, show that the two models present similar outcomes, despite their distinct nature, although there is a slightly better performance of the the pseudo-deterministic model in practice.

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