In this paper, we have combined the use of Self Organizing Maps with Gaussian Mixture Models, in order to enable situation awareness by detecting deviations ...
Supporting Maritime Situation Awareness Using Self Organizing ...
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Mar 5, 2019 · In this paper, we have combined the use of Self Organizing Maps with Gaussian Mixture Models, in order to enable situation awareness by ...
In this paper, we have combined the use of Self Organizing Maps with Gaussian Mixture Models, in order to enable situation awareness by detecting deviations ...
In this paper, we propose such a framework: a probabilistic normalcy model of vessel dynamics is learned using unsupervised techniques applied on historical S- ...
Supporting Maritime Situation Awareness Using Self Organizing Maps and Gaussian Mixture Models. Riveiro, M., Johansson, F., Falkman, G., & Ziemke, ...
In this paper, we have combined the use of Self Organizing Maps with Gaussian Mixture Models, in order to enable situation awareness by detecting deviations ...
In this paper, we present a network anomaly detection technique based on Probabilistic Self-Organizing Maps (PSOM) to differentiate between normal and anomalous ...
Riveiro, M., Johansson, F., Falkman, G., Ziemke, T. (2008b). Supporting maritime situation awareness using self organizing maps and gaussian mixture models.
[PDF] AI-Based Anomaly Detection in Maritime Tra c - Research Square
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Oct 31, 2024 · An unsupervised approach is a combination of a self-organizing map (SOM) and a Gaus- sian mixture model (GMM) the approach may be considered as ...
Sep 18, 2020 · In this article, we review link prediction techniques for situation awareness in a maritime context, and draw conclusions on how the addition of ...