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Data
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First-Spike-Based Visual Categorization Using Reward-Modulated STDP (Mozafari et al. 2018)
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Milad Mozafari
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"...Here, for the first time,
we show that (Reinforcement Learning) RL can be used efficiently to train a spiking neural
network (SNN) to perform object recognition in natural images
without using an external classifier. We used a feedforward
convolutional SNN and a temporal coding scheme where the
most strongly activated neurons fire first, while less activated
ones fire later, or not at all. In the highest layers, each neuron
was assigned to an object category, and it was assumed that
the stimulus category was the category of the first neuron to
fire. ..."
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Abstract integrate-and-fire neuron Show
Other
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Mozafari M, Kheradpisheh SR, Masquelier T, Nowzari-Dalini A, Ganjtabesh M (2018) Show
Other
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Mozafari, Milad [milad.mozafari at ut.ac.ir] Show
Other
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milad.mozafari@ut.ac.ir
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Temporal Coding
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Microsoft C# Program
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Mozafari, Milad [milad.mozafari at ut.ac.ir]
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M. Mozafari, S. R. Kheradpisheh, T. Masquelier, A. Nowzari-Dalini and M. Ganjtabesh, "First-Spike-Based Visual Categorization Using Reward-Modulated STDP," in IEEE Transactions on Neural Networks and Learning Systems.
doi: 10.1109/TNNLS.2018.2826721
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