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30 de may. de 2024 · A data anomaly is any deviation or irregularity in a dataset that does not conform to expected patterns or behaviors. These anomalies can manifest in various forms, such as outliers, unexpected patterns, or errors.
10 de jun. de 2024 · Anomaly detection is the process of analyzing company data to find data points that don’t align with a company's standard data pattern. Companies use anomalous activity detection to define system baselines, identify deviations from that baseline, and investigate inconsistent data.
31 de may. de 2024 · This survey paper presents a comprehensive and conceptual overview of anomaly detection using dynamic graphs. We focus on existing graph-based anomaly detection (AD) techniques and their applications to dynamic networks.
30 de may. de 2024 · Anomaly detection is the process of identifying samples in a dataset that diverge from some expected pattern. This process has wide applications in several industries such as API security, financial fraud and manufacturing defect detection.
2 de jun. de 2024 · To the best of our understanding, we demonstrate, for the first time, the vulnerability of deep-learning-based ADS-B time series unsupervised anomaly detection models to adversarial examples, which is a crucial step in safety-critical and cost-critical Air Traffic Management (ATM).
5 de jun. de 2024 · Visual anomaly detection aims to identify anomalous regions in images through unsupervised learning paradigms, with increasing application demand and value in fields such as industrial inspection and medical lesion detection.
12 de jun. de 2024 · Anomaly Detection is basically a technique to identify rare events or observations. These events or the observations can be a cause of suspicious activity. Because these observations are statistically different from the rest of the observations.
