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Uncertainty Quantification and Resource-Demanding Computer Vision Applications of Deep Learning., , , , , , and . CoRR, (2022)Entropy Maximization and Meta Classification for Out-Of-Distribution Detection in Semantic Segmentation., , and . CoRR, (2020)Have We Ever Encountered This Before? Retrieving Out-of-Distribution Road Obstacles from Driving Scenes., , , , , and . CoRR, (2023)The Ethical Dilemma When (Not) Setting up Cost-Based Decision Rules in Semantic Segmentation., , , , , and . CVPR Workshops, page 1395-1403. Computer Vision Foundation / IEEE, (2019)Two Video Data Sets for Tracking and Retrieval of Out of Distribution Objects., , , , and . ACCV (5), volume 13845 of Lecture Notes in Computer Science, page 476-494. Springer, (2022)Controlled False Negative Reduction of Minority Classes in Semantic Segmentation., , , , and . IJCNN, page 1-8. IEEE, (2020)Prediction Error Meta Classification in Semantic Segmentation: Detection via Aggregated Dispersion Measures of Softmax Probabilities., , , , , , and . IJCNN, page 1-9. IEEE, (2020)Images of desire: food-craving activation during fMRI., , , , and . NeuroImage, 23 (4): 1486-1493 (2004)MetaFusion: Controlled False-Negative Reduction of Minority Classes in Semantic Segmentation., , , , and . CoRR, (2019)What should AI see? Using the Public's Opinion to Determine the Perception of an AI., , , , , , , , , and . CoRR, (2022)