%0 Journal Article %1 siedel2022utilizing %A Siedel, G. %A Vock, S. %A Morozov, A. %A Voß, S. %D 2022 %J The IJCAI-ECAI-22 Workshop on Artificial Intelligence Safety (AISafety 2022) %K 2022ias ias %T Utilizing Class Separation Distance for the Evaluation of Corruption Robustness of Machine Learning Classifiers

@article{siedel2022utilizing, added-at = {2022-12-01T16:28:36.000+0100}, author = {Siedel, G. and Vock, S. and Morozov, A. and Voß, S.}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2cacd6a60f5faa369da6ffcd4ea2eeb7d/taylansngerli}, interhash = {a877e26452acce330455a8447ec3e0f5}, intrahash = {cacd6a60f5faa369da6ffcd4ea2eeb7d}, journal = {The IJCAI-ECAI-22 Workshop on Artificial Intelligence Safety (AISafety 2022)}, keywords = {2022ias ias}, timestamp = {2022-12-01T15:28:36.000+0100}, title = {Utilizing Class Separation Distance for the Evaluation of Corruption Robustness of Machine Learning Classifiers}, year = 2022 }