N-omniglot, a large-scale neuromorphic dataset for spatio-temporal sparse few-shot learning

HIGHLIGHTS

• who: Yang Li from the Chinese Academy of Sciences, Beijing, ChinaUniversity of have published the paper: N-Omniglot, a large-scale neuromorphic dataset for spatio-temporal sparse few-shot learning, in the Journal: (JOURNAL) of 15/Nov/2022
• what: To tackle the problems and fulfill this gap to the best of the knowledge the authors propose the first neuromorphic dataset for few-shot learning using SNNs: The authors provide several improved classic few-shot learning algorithms to adapt to SNN showing that varies in time dimension provides more temporal information and supports many tasks. The . . .
  

   

  

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