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Addressing Deep Learning Model Calibration Using Evidential Neural Networks And Uncertainty-Aware Training
In terms of accuracy, deep learning (DL) models have had considerable success in classification problems for medical imaging applications. However, it is well-known that the outputs of such models, which typically utilise the SoftMax function in the final classification layer can be over-confident,...
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| Publicado no: | Proc IEEE Int Symp Biomed Imaging |
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| Main Authors: | , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2023
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7616424/ https://ncbi.nlm.nih.gov/pubmed/39253557 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/ISBI53787.2023.10230515 |
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