Shared Map Convolutional Neural Networks for Real-Time Mobile Image Recognition

Raveane, William; González Arrieta, María Angélica

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Shared Map Convolutional Neural Networks for Real-Time Mobile Image Recognition

dc.contributor.author	Raveane, William
dc.contributor.author	González Arrieta, María Angélica
dc.date.accessioned	2017-09-06T09:17:02Z
dc.date.available	2017-09-06T09:17:02Z
dc.date.issued	2014-06
dc.identifier.citation	Distributed Computing and Artificial Intelligence, 11th International Conference. Advances in Intelligent Systems and Computing. Volumen 290, pp. 485-492.
dc.identifier.isbn	978-3-319-07592-1(Print) / 978-3-319-07593-8(Online)
dc.identifier.issn	2194-5357(Print) / 2194-5365(Online)
dc.identifier.uri	http://dx.doi.org/10.1007/978-3-319-07593-8_56
dc.identifier.uri	http://hdl.handle.net/10366/135149
dc.description.abstract	We present a technique for improving the speed of a convolutional neural network applied to large input images through the optimization of the sliding window approach. Meaningful performance gains and memory bandwidth reduction can be obtained by processing images in this manner, factors which play a crucial role in the deployment of deep neural networks within mobile devices.
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.publisher	Springer Science + Business Media
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Unported
dc.rights.uri	https://creativecommons.org/licenses/by-nc-nd/3.0/
dc.subject	Computer Science
dc.title	Shared Map Convolutional Neural Networks for Real-Time Mobile Image Recognition
dc.type	info:eu-repo/semantics/conferenceObject
dc.rights.accessRights	info:eu-repo/semantics/openAccess