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Learning to Recognize Actions From Limited Training Examples Using a Recurrent Spiking Neural Model
A fundamental challenge in machine learning today is to build a model that can learn from few examples. Here, we describe a reservoir based spiking neural model for learning to recognize actions with a limited number of labeled videos. First, we propose a novel encoding, inspired by how microsaccade...
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| Pubblicato in: | Front Neurosci |
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| Autori principali: | , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Frontiers Media S.A.
2018
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5840233/ https://ncbi.nlm.nih.gov/pubmed/29551962 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2018.00126 |
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