Deep Ensembles Are Robust to Occasional Catastrophic Failures of Individual DNNs for Organs Segmenta...
Deep Ensembles Are Robust to Occasional Catastrophic Failures of Individual DNNs for Organs Segmentations in CT Images
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Publisher
Cham: Springer International Publishing
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Language
English
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Cham: Springer International Publishing
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Contents
Deep neural networks (DNNs) have recently showed remarkable performance in various computer vision tasks, including classification and segmentation of medical images. Deep ensembles (an aggregated prediction of multiple DNNs) were shown to improve a DNN’s performance in various classification tasks. Here we explore how deep ensembles perform in the...
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Full title
Deep Ensembles Are Robust to Occasional Catastrophic Failures of Individual DNNs for Organs Segmentations in CT Images
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10502003
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_10502003
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ISSN
1618-727X,0897-1889
E-ISSN
1618-727X
DOI
10.1007/s10278-023-00857-2
