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Poster : Advanced Feature Based Deep Learning for Intell..:

, In: Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion,

Ramasinghe, Sameera - p. 75 ff. , 2016

Link: https://dl.acm.org/doi/10.1145/2938559.2948813

RT 
T1 <cTitle>Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion</cTitle>: T1 <Title>Poster				: Advanced Feature Based Deep Learning for Intelligent Human Activity Recognition: An Approach using Scene Context and Composition of Sub Events.</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-2948813&Exemplar=1&LAN=DE
				
A1 Ramasinghe, Sameera
PB ACM
YR 2016
K1 action recognition
K1 deep learning
K1 lstm
K1 rnn
K1 Computing methodologies
K1 Machine learning
K1 Learning settings
K1 Semi-supervised learning settings
K1 Machine learning approaches
K1 Learning latent representations
K1 Deep belief networks
K1 Learning paradigms
K1 Supervised learning
K1 Supervised learning by classification
K1 Batch learning
K1 Theory of computation
K1 Theory and algorithms for application domains
K1 Machine learning theory
K1 Kernel methods
K1 Support vector machines
SP 75 ff.
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/2938559.2948813
DO https://dl.acm.org/doi/10.1145/2938559.2948813
SF ELIB - SuUB Bremen

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