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First-Spike-Based Visual Categorization Using Reward-Modulated STDP (Mozafari et al. 2018)
Milad Mozafari
MozafariEtAl2018 [14746015]
"...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. ..."
  • Abstract integrate-and-fire neuron Show Other
  • Mozafari M, Kheradpisheh SR, Masquelier T, Nowzari-Dalini A, Ganjtabesh M (2018) Show Other
  • Mozafari, Milad [milad.mozafari at ut.ac.ir] Show Other
milad.mozafari@ut.ac.ir
Temporal Coding
Microsoft C# Program
Mozafari, Milad [milad.mozafari at ut.ac.ir]
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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Revisions: 12
Last Time: 10/17/2018 5:35:28 PM
Reviewer: Tom Morse - MoldelDB admin
Owner: Tom Morse - MoldelDB admin