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Leveraging Self-Supervised Learning for Human Activity Reco..:

, In: Proceedings of the 2023 ACM Conference on Information Technology for Social Good,

Chen, Hui ; Gouin-Vallerand, Charles ; Bouchard, Kévin... - p. 324-332 , 2023

Link: https://dl.acm.org/doi/10.1145/3582515.3609551

RT 
T1 <cTitle>Proceedings of the 2023 ACM Conference on Information Technology for Social Good</cTitle>: T1 <Title>Leveraging Self-Supervised Learning for Human Activity Recognition with Ambient Sensors</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3609551&Exemplar=1&LAN=DE
				
A1 Chen, Hui
A1 Gouin-Vallerand, Charles
A1 Bouchard, Kévin
A1 Gaboury, Sébastien
A1 Couture, Mélanie
A1 Bier, Nathalie
A1 Giroux, Sylvain
PB ACM
YR 2023
K1 SimCLR framework
K1 ambient sensors
K1 human activity recognition
K1 self-supervised learning
K1 Computing methodologies
K1 Artificial intelligence
K1 Computer vision
K1 Computer vision tasks
K1 Activity recognition and understanding
K1 Applied computing
K1 Life and medical sciences
K1 Health care information systems
K1 Machine learning
K1 Machine learning approaches
K1 Learning latent representations
SP 324
OP 332
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3582515.3609551
DO https://dl.acm.org/doi/10.1145/3582515.3609551
SF ELIB - SuUB Bremen

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