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Tobias Riedlinger

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Deep Active Learning with Noisy Oracle in Object Detection

Sep 30, 2023
Marius Schubert, Tobias Riedlinger, Karsten Kahl, Matthias Rottmann

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LMD: Light-weight Prediction Quality Estimation for Object Detection in Lidar Point Clouds

Jun 15, 2023
Tobias Riedlinger, Marius Schubert, Sarina Penquitt, Jan-Marcel Kezmann, Pascal Colling, Karsten Kahl, Lutz Roese-Koerner, Michael Arnold, Urs Zimmermann, Matthias Rottmann

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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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Pixel-wise Gradient Uncertainty for Convolutional Neural Networks applied to Out-of-Distribution Segmentation

Mar 13, 2023
Kira Maag, Tobias Riedlinger

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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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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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