Explaining and upsampling anomalies in time-series sensor data.
(2022)
Conference Proceeding
PIRIE, C. 2022. Explaining and upsampling anomalies in time-series sensor data. In Reuss, P. and Schönborn, J. (eds). ICCBR-DC 2022: proceedings of the 30th International conference on case-based reasoning doctorial consortium 2022 (ICCBR-DC 2022), co-located with the 30th International conference on case-based reasoning 2022 (ICCBR 2022), 12-15 September 2022, Nancy, France. Aachen: CEUR workshop proceedings [online], 3418, pages 1-14. Available from: https://ceur-ws.org/Vol-3418/ICCBR_2022_DC_paper13.pdf
The aims of this research was to improve anomaly detection methods in multi-sensor data by extending current re-sampling and explanation methods to work in a time-series setting. While there is a plethora of literature surrounding XAI for tabular dat... Read More about Explaining and upsampling anomalies in time-series sensor data..