Uncertainty Estimation for Deep Learning-Based Segmentation of Roads in Synthetic Aperture Radar Ima...
Uncertainty Estimation for Deep Learning-Based Segmentation of Roads in Synthetic Aperture Radar Imagery
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Basel: MDPI AG
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Language
English
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Basel: MDPI AG
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Mission-critical applications that rely on deep learning (DL) for automation suffer because DL models struggle to provide reliable indicators of failure. Reliable failure prediction can greatly improve the efficiency of a system, because it becomes easier to predict when human intervention is required. DL-based systems thus stand to benefit greatly...
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Uncertainty Estimation for Deep Learning-Based Segmentation of Roads in Synthetic Aperture Radar Imagery
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TN_cdi_doaj_primary_oai_doaj_org_article_f3effc4660b7448a8189ad63e797633f
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_f3effc4660b7448a8189ad63e797633f
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ISSN
2072-4292
E-ISSN
2072-4292
DOI
10.3390/rs13081472
