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20232026
most citedAn affordable hardware-aware neural architecture search for deploying convolutional neural networks on ultra-low-power computing platforms

17 citations · 37 across the 14 of their papers we have counts for

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cs.AR2026★ 7 cited

Running hardware-aware neural architecture search on embedded devices under 512MB of RAM

Andrea Mattia Garavagno, Edoardo Ragusa, Paolo Gastaldo +1

This document proposes a novel approach to hardware-aware neural architecture search (HW NAS) that considers the resources available on the computing platform running it, enabling…