Scalable and accurate online multivariate anomaly detection
The continuous monitoring of dynamic processes generates vast amounts of streaming
multivariate time series data. Detecting anomalies within them is crucial for real-time …
multivariate time series data. Detecting anomalies within them is crucial for real-time …
Multi-Scale Event Detection in Financial Time Series
DS de Salles, C Gea, CE Mello, L Assis… - Computational …, 2024 - Springer
Abstract Information published in the communication media, such as government transitions,
economic crises, or corruption scandals, is an external factor associated with financial time …
economic crises, or corruption scandals, is an external factor associated with financial time …
Using deep neural networks to detect non-analytically defined expert event labels in canoe sprint force sensor signals
S Rockstroh, P Frenzel, D Matthes… - … Workshop on Sport …, 2024 - ieeexplore.ieee.org
Assessing an athlete's performance in canoe sprint is often established by measuring a
variety of kinematic parameters during training sessions. Many of these parameters are …
variety of kinematic parameters during training sessions. Many of these parameters are …
Anticipation, earliness, alarm cardinality: A new metric for industrial time-series anomaly detection
Among the increasingly adopted data-driven solutions in various industrial processes, Time-
Series-based Anomaly Detection (TSAD) became a hot topic in the past few years. As the …
Series-based Anomaly Detection (TSAD) became a hot topic in the past few years. As the …