Abstract:
This article introduces FSL-HDnn, an energy-efficient accelerator that implements the end-to-end pipeline of feature extraction (FE) and on-device few-shot learning (FSL). The accelerator addresses fundamental challenges of on-device learning (ODL) for resource-constrained edge applications through two synergistic modules: a parameter-efficient feature extractor (FE) employing weight clustering and an FSL classifier …