Ensembles of Compact, Region-specific & Regularized Spiking Neural Networks for Scalable Place Recognition. (arXiv:2209.08723v3 [cs.CV] UPDATED)

Spiking neural networks have significant potential utility in robotics due to
their high energy efficiency on specialized hardware, but proof-of-concept
implementations have not yet typically achieved competitive performance or
capability with conventional approaches. In this paper, we tackle one of the
key practical challenges of scalability by introducing a novel modular ensemble
network approach, where compact, localized spiking networks each learn and are
solely responsible for recognizing places in a local region of the environment
only. This modular approach creates …

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