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How can we learn (more) from challenges? A statistical approach to driving future algorithm development., , , , , , , , , и 5 other автор(ы). CoRR, (2021)Beyond rankings: Learning (more) from algorithm validation., , , , , , , , , и 7 other автор(ы). Medical Image Anal., (мая 2023)Understanding Automatic Diagnosis and Classification Processes with Data Visualization., , , и . ICHMS, стр. 1-6. IEEE, (2020)Data Augmentation: a Combined Inductive-Deductive Approach featuring Answer Set Programming., , , и . CoRR, (2023)Using CNNs for Designing and Implementing an Automatic Vascular Segmentation Method of Biomedical Images., , , , , , и . AI*IA, том 11298 из Lecture Notes in Computer Science, стр. 60-70. Springer, (2018)Classification and Survival Prediction in Diffuse Large B-Cell Lymphoma by Gene Expression Profiling., , и . LOD, том 11331 из Lecture Notes in Computer Science, стр. 166-178. Springer, (2018)μ-Net: A Deep Learning-Based Architecture for μ-CT Segmentation., , , , , , , , , и 5 other автор(ы). CoRR, (2024)Comparative validation of multi-instance instrument segmentation in endoscopy: Results of the ROBUST-MIS 2019 challenge., , , , , , , , , и 40 other автор(ы). Medical Image Anal., (2021)Continual Learning for medical image classification., , и . HC@AIxIA, том 3307 из CEUR Workshop Proceedings, стр. 67-76. CEUR-WS.org, (2022)Combining Deep Learning and ASP-Based Models for the Semantic Segmentation of Medical Images., , , и . RuleML+RR, том 12851 из Lecture Notes in Computer Science, стр. 95-110. Springer, (2021)