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Energy-Efficient ConvNets Through Approximate Computing

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Record title

Energy-Efficient ConvNets Through Approximate Computing

Record identifier

TN_cdi_proquest_journals_2080712198

Energy-Efficient ConvNets Through Approximate Computing

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https://collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2080712198

Energy-Efficient ConvNets Through Approximate Computing

Full title

Energy-Efficient ConvNets Through Approximate Computing

Publisher

Ithaca: Cornell University Library, arXiv.org

Journal title

arXiv.org, 2016

Record Identifier

TN_cdi_proquest_journals_2080712198

Language

English

Publication information

Publisher

Ithaca: Cornell University Library, arXiv.org

More information

SCOPE AND CONTENTS

Contents

Recently ConvNets or convolutional neural networks (CNN) have come up as state-of-the-art classification and detection algorithms, achieving near-human performance in visual detection. However, ConvNet algorithms are typically very computation and memory intensive. In order to be able to embed ConvNet-based classification into wearable platforms an...

ALTERNATIVE TITLES

Full title

Energy-Efficient ConvNets Through Approximate Computing

AUTHORS, ARTISTS AND CONTRIBUTORS

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PRIMARY IDENTIFIERS

Record Identifier

TN_cdi_proquest_journals_2080712198

Permalink

https://collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2080712198

OTHER IDENTIFIERS

E-ISSN

2331-8422

DOI

10.1109/WACV.2016.7477614

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