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3E-Net: Entropy-Based Elastic Ensemble of Deep Convolutional Neural Networks for Grading of Invasive Breast Carcinoma Histopathological Microscopic Images
Automated grading systems using deep convolution neural networks (DCNNs) have proven their capability and potential to distinguish between different breast cancer grades using digitized histopathological images. In digital breast pathology, it is vital to measure how confident a DCNN is in grading u...
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| Publicado no: | Entropy (Basel) |
|---|---|
| Main Authors: | , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
MDPI
2021
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8156865/ https://ncbi.nlm.nih.gov/pubmed/34065765 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e23050620 |
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