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Leveraging SO(3)-steerable convolutions for pose-robust semantic segmentation in 3D medical data
Convolutional neural networks (CNNs) allow for parameter sharing and translational equivariance by using convolutional kernels in their linear layers. By restricting these kernels to be SO(3)-steerable, CNNs can further improve parameter sharing. These rotationally-equivariant convolutional layers h...
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| Pubblicato in: | J Mach Learn Biomed Imaging |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7617181/ https://ncbi.nlm.nih.gov/pubmed/39655282 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.59275/j.melba.2024-7189 |
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