1 citations · 1 across the 2 of their papers we have counts for
2 papers
eess.IV2022
Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation
Camila Gonzalez, Karol Gotkowski, Moritz Fuchs +5
Automatic segmentation of ground glass opacities and consolidations in chest computer tomography (CT) scans can potentially ease the burden of radiologists during times of high res…
eess.IV2021★ 1 cited
Quality monitoring of federated Covid-19 lesion segmentation
Camila Gonzalez, Christian Harder, Amin Ranem +5
Federated Learning is the most promising way to train robust Deep Learning models for the segmentation of Covid-19-related findings in chest CTs. By learning in a decentralized fas…