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  • Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Datasets Using Deep Learning 

    Authors:Karadayı, Yıldız
    Publisher and Date:(Springer, 2020)
    Techniques used for spatio-temporal anomaly detection in an unsupervised settings has attracted great attention in recent years. It has extensive use in a wide variety of applications such as: medical diagnosis, sensor events analysis, earth science, fraud detection systems, etc. Most of the real world time series datasets have spatial dimension as additional context such as geographic location. Although many temporal data are spatio-temporal in nature, existing techniques are limited to handle ...