The University of Southampton
University of Southampton Institutional Repository

TinyOps: ImageNet Scale Deep Learning on Microcontrollers

TinyOps: ImageNet Scale Deep Learning on Microcontrollers
TinyOps: ImageNet Scale Deep Learning on Microcontrollers
Data obtained in TinyOps: ImageNet Scale Deep Learning on Microcontrollers research. To support a paper to be presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops 2022
University of Southampton
Sadiq, Sulaiman
e82e1fe2-6b8c-4c49-b051-8aef0dabe99a
Sadiq, Sulaiman
e82e1fe2-6b8c-4c49-b051-8aef0dabe99a

Sadiq, Sulaiman (2022) TinyOps: ImageNet Scale Deep Learning on Microcontrollers. University of Southampton doi:10.5258/SOTON/D2188 [Dataset]

Record type: Dataset

Abstract

Data obtained in TinyOps: ImageNet Scale Deep Learning on Microcontrollers research. To support a paper to be presented at IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops 2022

Text
README_Sadiq.txt - Dataset
Download (3kB)
Text
Fig3b.csv - Dataset
Available under License Creative Commons Attribution.
Download (55B)
Text
Table1.csv - Dataset
Available under License Creative Commons Attribution.
Download (103B)
Text
Table2.csv - Dataset
Download (813B)
Text
Fig3a.csv - Dataset
Available under License Creative Commons Attribution.
Download (85B)
Text
Table3.csv - Dataset
Available under License Creative Commons Attribution.
Download (232B)

Show all 6 downloads.

More information

Published date: 2022

Identifiers

Local EPrints ID: 468157
URI: http://eprints.soton.ac.uk/id/eprint/468157
PURE UUID: e9797ffc-2237-4a62-bff2-f61dfafe27f3

Catalogue record

Date deposited: 04 Aug 2022 16:37
Last modified: 05 May 2023 19:35

Export record

Altmetrics

Contributors

Creator: Sulaiman Sadiq

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×