31.10.2022
MCML at ACM SIGSPATIAL 2022
Two Accepted Papers (1 Main, and 1 Workshop)
30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Seattle, WA, USA, Nov 01-04, 2022
We are happy to announce that MCML researchers have contributed a total of 2 papers to ACM SIGSPATIAL 2022: 1 Main, and 1 Workshop papers. Congrats to our researchers!
Main Track (1 paper)
M. Bernhard • M. Schubert
Robust Object Detection in Remote Sensing Imagery with Noisy and Sparse Geo-Annotations.
ACM SIGSPATIAL 2022 - 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle, WA, USA, Nov 01-04, 2022. DOI GitHub
Robust Object Detection in Remote Sensing Imagery with Noisy and Sparse Geo-Annotations.
ACM SIGSPATIAL 2022 - 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle, WA, USA, Nov 01-04, 2022. DOI GitHub
Workshops (1 paper)
A. Lohrer • J. J. Binder • P. Kröger
Group Anomaly Detection for Spatio-Temporal Collective Behaviour Scenarios in Smart Cities.
IWCTS @ACM SIGSPATIAL 2022 - 15th International Workshop on Computational Transportation Science at the 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle, WA, USA, Nov 01-04, 2022. DOI
Group Anomaly Detection for Spatio-Temporal Collective Behaviour Scenarios in Smart Cities.
IWCTS @ACM SIGSPATIAL 2022 - 15th International Workshop on Computational Transportation Science at the 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems. Seattle, WA, USA, Nov 01-04, 2022. DOI
Related
26.08.2026
Transparency for Global Health Aid
MCML PI Stefan Feuerriegel and his team use machine learning to uncover disparities in the global allocation of health aid.
25.08.2026
David Rügamer: We Need Uncertainty Quantification
MCML PI David Rügamer explains why uncertainty quantification is essential for building trustworthy AI and making informed decisions.