Revisiting vicinal risk minimization for partially supervised multi-label classification under data scarcity
Due to the high human cost of annotation, it is nontrivial to curate a large-scale medical dataset that is fully labeled for all classes of interest. Instead, it would be convenient to collect multiple small partially labeled datasets from different matching sources, where the medical images may hav...
| Hoofdauteurs: | , , |
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| Formaat: | Conference item |
| Taal: | English |
| Gepubliceerd in: |
IEEE
2022
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