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pro vyhledávání: '"Mehrtens, Hendrik A."'
Deep Neural Networks have shown promising classification performance when predicting certain biomarkers from Whole Slide Images in digital pathology. However, the calibration of the networks' output probabilities is often not evaluated. Communicating
Externí odkaz:
http://arxiv.org/abs/2312.09719
In the past years, deep learning has seen an increase in usage in the domain of histopathological applications. However, while these approaches have shown great potential, in high-risk environments deep learning models need to be able to judge their
Externí odkaz:
http://arxiv.org/abs/2301.01054
Calibration and uncertainty estimation are crucial topics in high-risk environments. We introduce a new diversity regularizer for classification tasks that uses out-of-distribution samples and increases the overall accuracy, calibration and out-of-di
Externí odkaz:
http://arxiv.org/abs/2201.10908
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