… use a modified anomaly detection metric. Specifically, if any frame in the ground truth
anomaly segment is detected by our dynamic threshold, we consider the segment to be detected …

… , precision, and complexity that are inherent in many anomaly detection scenarios. We also
propose a novel dynamic thresholding approach that does not rely on scarce labels or false …

… the anomalies with a dynamic thresholding algorithm, to improve the robustness of our
anomaly detector. … In Section III, we introduce our dynamic thresholding algorithm. In Section IV, …

… amount of unsupervised anomaly detection methods have … approach is potentially detecting
anomalies in novel classes … 22], not solving the anomaly detection task described in this work…

… We first describe four types of anomalies that arise in dynamic networks, providing an intuitive
… use a threshold system as an anomaly detector, GraphScope uses a dynamic threshold, …

… that dynamic thresholding … a dynamic thresholding strategy and LSTMs, both of which make
use of contextual data, is investigated in this paper as an improvement of anomaly detection …

… focused on static thresholds for detecting abnormalities, we introduce a dynamic threshold
approach that significantly improves the efficiency of automatic fault detection. Additionally, …

… is fed to the threshold method to detect the anomalous data. … a threshold value as input to
the detection algorithm, we presented a dynamic threshold generation method in the detection …

… of anomaly detection for coal-rock dynamic disasters, this paper proposes an anomaly detection
method based on a dynamic threshold … used as the initial threshold, and the subsequent …

… 𝑋â|àâ whose prediction error is larger than 𝑇 as an anomaly. … anomaly detection, an LSTM
network is used as the predictor in this paper. For anomaly extraction, a dynamic thresholding …