Dec 18, 2019 · First, it introduces the DTW algorithm and identifies whether the perceived data are the signals of disasters based on the similarity fitting ...
The identification method proposed in this article first takes advantages of the dynamic time warping algorithm, which is widely applied in the field of audio ...
The current mine disaster event monitoring method is a lagged identification, which is based on monitoring a series of sensors with a 10-s-long data waveform as ...
Oct 24, 2024 · This work specifically focuses on the detection of anomalous activities in videos, employing the UCF crime database as the primary dataset. The ...
Apr 22, 2024 · We propose LogMS, a multi-stage log anomaly detection method based on multi-source information fusion and probability label estimation.
Sep 7, 2016 · This paper focuses on the monitoring of abnormal situation in workspace where complicate production activities are performed.
Apr 1, 2024 · K-means clustering is another multi-pass method that generates data clusters for finding abnormalities in the test dataset. Traditional anomaly ...
Multistage identification method for real-time abnormal events of streaming data. December 2019 · International Journal of Distributed Sensor Networks. Hao ...
In this position paper, we argue for the need of a new type of data stream analytics that can address anomaly detection and explanation discovery in a single, ...
Real-time anomaly detection for streaming data is distinct from batch anomaly detection. Streaming analytics calls for models and algorithms that can learn ...
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