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Semi-Supervised Classification of Noisy, Gigapixel Histology Images
One of the greatest obstacles in the adoption of deep neural networks for new medical applications is that training these models typically require a large amount of manually labeled training samples. In this body of work, we investigate the semi-supervised scenario where one has access to large amou...
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| Publicat a: | Proc IEEE Int Symp Bioinformatics Bioeng |
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| Autors principals: | , , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8144886/ https://ncbi.nlm.nih.gov/pubmed/34046246 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/BIBE50027.2020.00097 |
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