Maschinelles Lernen für Space Gardening

Working in the EDEN NEXT GEN and EDEN LUNA projects, we are concerned with detecting unhealthiness within different kinds of data.In this talk, I will introduce different classic and deep-learning-based methods for finding anomalies in time series data and present our latest results on the differences regarding the types of anomalies these methods can find. Based on this, I will present our concept for using these techniques to detect unhealthy system states in telemetry data as well as unhealthy plants in images.

Plattformunabhängige Web-Einwahl: https://confpool.vc.dlr.de/webapp/#/?conference=1907650545@vc.dlr.de