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S-TLLR: STDP-inspired Temporal Local Learning Rule for Spiking Neural Networks
Spiking Neural Networks (SNNs) are biologically plausible models that have been identified as potentially apt for deploying energy-efficient intelligence at the edge, particularly for sequential learning tasks.
Hardware/Software co-design with ADC-Less In-memory Computing Hardware for Spiking Neural Networks
Spiking Neural Networks (SNNs) are bio-plausible models that hold great potential for realizing energy-efficient implementations of sequential tasks on resource-constrained edge devices.
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Gesture Recognition
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