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Detecting failure modes in image reconstructions with interval neural network uncertainty
PURPOSE: The quantitative detection of failure modes is important for making deep neural networks reliable and usable at scale. We consider three examples for common failure modes in image reconstruction and demonstrate the potential of uncertainty quantification as a fine-grained alarm system. METH...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer International Publishing
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8616888/ https://www.ncbi.nlm.nih.gov/pubmed/34480723 http://dx.doi.org/10.1007/s11548-021-02482-2 |