Using atmospheric understanding to exploit multi-spectral images
Ankit Patnala published his first paper in the IEEE journal. There is yet more information currently unused by machine learning in satellite data. Natural images come in RGB and thus…
Can Deep Learning close the Gap between terrestrial modeled Data and Observations?
Within the HDS-LEE graduate school, Kaveh P. Yousefi presented his U-Net capable of improving model-based precipitation and surface pressure fields towards observations.
Jungle-Net Poster presentation
Within the HDS-LEE graduate school and the ISPRS congress Timo Stomberg presented his Jungle-Net capable of giving insights into wilderness using explainable machine learning.
Lecture on Explainable Machine Learning for Earth Science
The live stream of Prof. Dr. Ribana Roscher's lecture on explainable machine learning can be found here on YouTube. The lecture has two parts. The first part introduces all you…
Explainable Machine Learning for Air Quality
The article "Explainable machine learning reveals capabilities, reundancy, and limitations of a geospatial air quality benchmark dataset" is now available in the journal Machine Learning and Knowledge Extraction. Here you…
Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties
The preprint of the article “Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties” is now available here: https://doi.org/10.5194/gmd-2022-2 This work is a follow-up collaboration between…
Unboxing Black Boxes
If you are interested in the talk Scarlet Stadtler gave at CASUS, please check out this video here https://youtu.be/j1DLOoi0N5Y CASUS Institute Seminar, Dr. Scarlet Stadtler, Forschungszentrum Jülich GmbH/Jülich Supercomputing Centre (JSC)…
What is your research about?
There was a short article published in the "effzett" about KI:STE PI Scarlet Stadtler. It can be found here: https://effzett.fz-juelich.de/2-21/woran-forschen-sie-gerade (in German) You can find out more about Scarlet Stadtler…
Atmospheric Water Cycle and Remote Sensing
General Introduction The Institute for Geophysics and Meteorology at the University of Cologne is involved in geophysical exploration (from solar system, extrasolar planets, and moons) to our earth system's atmosphere…
How can explainable AI be used to understand what constitutes wilderness?
On July 8th Timo Stomberg, KI:STE doctoral researcher, presented jUngle-Net at the ISPRS Congress 2021. jUngle-Net is an explainable neural network which we use to gain new insights into the…