Spiking Neural Networks inspired by our understanding of observed biological structure and functions have been successfully applied to visual recognition/classification tasks. A new series of vision benchmarks for spike-based neural processing are now needed to quantitatively measure progress within this rapidly advancing field. A large dataset of spike-based visual stimuli is needed to provide a baseline for comparisons. Furthermore a complementary evaluation methodology is also crucial to assess the accuracy and efficiency of an algorithm. We can summarise existing models, propose the dataset and discuss about the evaluation methodology in order to promote meaningful comparison in the field of neural computation.

Last modified 4 years ago Last modified on 05/20/15 11:52:40

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