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Patch individual filter layers in CNNs to harness the spatial homogeneity of neuroimaging data
Convolutional neural networks (CNNs)—as a type of deep learning—have been specifically designed for highly heterogeneous data, such as natural images. Neuroimaging data, however, is comparably homogeneous due to (1) the uniform structure of the brain and (2) additional efforts to spatially normalize...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712523/ https://www.ncbi.nlm.nih.gov/pubmed/34961762 http://dx.doi.org/10.1038/s41598-021-03785-9 |