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EmBench : Quantifying Performance Variations of Deep Neu..:

, In: The 3rd International Workshop on Deep Learning for Mobile Systems and Applications,

Almeida, Mario ; Laskaridis, Stefanos ; Leontiadis, Ilias.. - p. 1-6 , 2019

Link: https://dl.acm.org/doi/10.1145/3325413.3329793

RT 
T1 <cTitle>The 3rd International Workshop on Deep Learning for Mobile Systems and Applications</cTitle>: T1 <Title>EmBench				: Quantifying Performance Variations of Deep Neural Networks across Modern Commodity Devices</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3329793&Exemplar=1&LAN=DE
				
A1 Almeida, Mario
A1 Laskaridis, Stefanos
A1 Leontiadis, Ilias
A1 Venieris, Stylianos I.
A1 Lane, Nicholas D.
PB ACM
YR 2019
K1 deep neural networks
K1 mobile devices
K1 on-device inference
K1 Human-centered computing
K1 Ubiquitous and mobile computing
K1 Ubiquitous and mobile devices
K1 Mobile devices
K1 Computing methodologies
K1 Machine learning
K1 Machine learning approaches
K1 Neural networks
K1 Computer systems organization
K1 Architectures
K1 Other architectures
K1 Artificial intelligence
K1 Computer vision
K1 Computer vision problems
K1 Object recognition
K1 Ubiquitous and mobile computing theory, concepts and paradigms
K1 Mobile computing
K1 Ubiquitous and mobile computing design and evaluation methods
SP 1
OP 6
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3325413.3329793
DO https://dl.acm.org/doi/10.1145/3325413.3329793
SF ELIB - SuUB Bremen

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