Results for Anomaly detection

Publications & Outputs

1. Multivariate Time Series Anomaly Scoring Dashboard

   Granados Garcia, G. C. (Artist), 21/11/2024

   Research output: Exhibits, objects and web-based outputs › Software

2. R Package AnomalyScore: Anomaly Scoring for Multivariate Time Series

   Granados Garcia, G. C. (Artist), 21/11/2024

   Research output: Exhibits, objects and web-based outputs › Software

3. HFN: Heterogeneous feature network for multivariate time series anomaly detection

   Zhan, J., Wu, C., Yang, C., Miao, Q. & Ma, X., 30/06/2024, In: Information Sciences. 670, 15 p., 120626.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

4. Condition monitoring of wind turbine using novel deep learning method and dynamic kernel principal components Mahalanobis distance

   Chen, W., Zhou, H., Cheng, L., Liu, J. & Xia, M., 31/10/2023, In: Engineering Applications of Artificial Intelligence. 125, 106757.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

5. Poisson-FOCuS: An Efficient Online Method for Detecting Count Bursts with Application to Gamma Ray Burst Detection

   Ward, K., Dilillo, G., Eckley, I. & Fearnhead, P., 6/09/2023, (E-pub ahead of print) In: Journal of the American Statistical Association. 13 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

6. 6G-Enabled Anomaly Detection for Metaverse Healthcare Analytics in Internet of Things

   Wu, X., Yang, Y., Bilal, M., Qi, L. & Xu, X., 24/07/2023, (E-pub ahead of print) In: IEEE Journal of Biomedical and Health Informatics. p. 1-10 10 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

7. Masked Swin Transformer Unet for Industrial Anomaly Detection

   Jiang, J., Zhu, J., Bilal, M., Cui, Y., Kumar, N., Dou, R., Su, F. & Xu, X., 1/02/2023, In: IEEE Transactions on Industrial Informatics. 19, 2, p. 2200-2209 10 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

8. STGAT-MAD: Spatial-Temporal Graph Attention Network for Multivariate Time Series Anomaly Detection

   Zhan, J., Wang, S., Ma, X., Wu, C., Yang, C., Zeng, D. & Wang, S., 27/04/2022, (ICASSP 2022) 2022 IEEE International Conference on Acoustics, Speech and Signal Processing, May 22-27, 2022, Singapore. IEEE, 5 p.

   Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

9. Innovative and Additive Outlier Robust Kalman Filtering with a Robust Particle Filter

   Fisch, A., Eckley, I. & Fearnhead, P., 31/01/2022, In: IEEE Transactions on Signal Processing. 70, p. 47-56 10 p.

   Research output: Contribution to Journal/Magazine › Journal article › peer-review

10. An evolving approach to data streams clustering based on typicality and eccentricity data analytics

    Bezerra, C. G., Costa, B. S. J., Guedes, L. A. & Angelov, P. P., 31/05/2020, In: Information Sciences. 518, p. 13-28 16 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

11. Robust Functional Regression for Outlier Detection

    Hullait, H., Leslie, D. S., Pavlidis, N. G. & King, S., 23/01/2020, Advanced Analytics and Learning on Temporal Data: 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers. Lemaire, V., Malinowski, S., Bagnall, A., Bondu, A., Guyet, T. & Tavenard, R. (eds.). Cham: Springer, p. 3-13 11 p. (Lecture Notes in Computer Science; vol. 11986).

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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