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Identifying Label Errors in Object Detection Datasets by Loss Inspection


Mar 13, 2023
Marius Schubert, Tobias Riedlinger, Karsten Kahl, Daniel Kröll, Sebastian Schoenen, Siniša Šegvić, Matthias Rottmann

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Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection


Dec 21, 2022
Tobias Riedlinger, Marius Schubert, Karsten Kahl, Hanno Gottschalk, Matthias Rottmann

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* 17 pages, 12 figures, 9 tables 

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Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning


May 30, 2022
Julian Burghoff, Robin Chan, Hanno Gottschalk, Annika Muetze, Tobias Riedlinger, Matthias Rottmann, Marius Schubert

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Gradient-Based Quantification of Epistemic Uncertainty for Deep Object Detectors


Jul 09, 2021
Tobias Riedlinger, Matthias Rottmann, Marius Schubert, Hanno Gottschalk

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* 20 pages, 8 figures, 7 tables 

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MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection


Oct 06, 2020
Marius Schubert, Karsten Kahl, Matthias Rottmann

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* 11 pages, 5 figures, 5 tables 

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Uncertainty Measures and Prediction Quality Rating for the Semantic Segmentation of Nested Multi Resolution Street Scene Images


Apr 09, 2019
Matthias Rottmann, Marius Schubert

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