Embedded Binarized Neural Networks

Abstract

We study embedded Binarized Neural Networks (eBNNs) with the aim of allowing current binarized neural networks (BNNs) in the literature to perform feedforward inference efficiently on small embedded devices. We focus on minimizing the required memory footprint, given that these devices often have memory as small as tens of kilobytes (KB). Beyond minimizing… (More)

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Cite this paper

@inproceedings{McDanel2017EmbeddedBN, title={Embedded Binarized Neural Networks}, author={Bradley McDanel and Surat Teerapittayanon and H. T. Kung}, booktitle={EWSN}, year={2017} }