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Anomaly and Novelty detection for Satellite and Drone syste..:

, In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management,

Tariq, Shahroz ; Chung, Daewon ; Woo, Simon. - p. 5294-5295 , 2023

Link: https://dl.acm.org/doi/10.1145/3583780.3615306

RT 
T1 <cTitle>Proceedings of the 32nd ACM International Conference on Information and Knowledge Management</cTitle>: T1 <Title>Anomaly and Novelty detection for Satellite and Drone systems (ANSD '23)</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3615306&Exemplar=1&LAN=DE
				
A1 Tariq, Shahroz
A1 Chung, Daewon
A1 Woo, Simon
A1 Shin, Youjin
PB ACM
YR 2023
K1 aerial data
K1 anomaly detection
K1 artificial intelligence
K1 clustering
K1 data mining
K1 deep learning
K1 drones
K1 geospatial analysis
K1 novelty detection
K1 satellite
K1 telemetry data
K1 Information systems
K1 Information systems applications
K1 Data mining
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Unsupervised learning
K1 Anomaly detection
K1 Artificial intelligence
K1 Computer vision
K1 Mathematics of computing
K1 Probability and statistics
K1 Statistical paradigms
K1 Time series analysis
SP 5294
OP 5295
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3583780.3615306
DO https://dl.acm.org/doi/10.1145/3583780.3615306
SF ELIB - SuUB Bremen

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