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Ball Trajectory Inference from Multi-Agent Sports Contexts ..:

, In: Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,

Kim, Hyunsung ; Choi, Han-Jun ; Kim, Chang Jo.. - p. 4296-4307 , 2023

Link: https://dl.acm.org/doi/10.1145/3580305.3599779

RT 
T1 <cTitle>Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>Ball Trajectory Inference from Multi-Agent Sports Contexts Using Set Transformer and Hierarchical Bi-LSTM</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3599779&Exemplar=1&LAN=DE
				
A1 Kim, Hyunsung
A1 Choi, Han-Jun
A1 Kim, Chang Jo
A1 Yoon, Jinsung
A1 Ko, Sang-Ki
PB ACM
YR 2023
K1 multi-agent analysis
K1 player tracking data
K1 spatiotemporal data analysis
K1 sports analytics
K1 trajectory inference
K1 Information systems
K1 Information systems applications
K1 Spatial-temporal systems
K1 Computing methodologies
K1 Machine learning
K1 Machine learning approaches
K1 Neural networks
K1 Artificial intelligence
K1 Knowledge representation and reasoning
K1 Spatial and physical reasoning
K1 Learning latent representations
SP 4296
OP 4307
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3580305.3599779
DO https://dl.acm.org/doi/10.1145/3580305.3599779
SF ELIB - SuUB Bremen

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