Sparse convolutional neural network for high-resolution skull shape completion and shape super-resolution
Abstract Traditional convolutional neural network (CNN) methods rely on dense tensors, which makes them suboptimal for spatially sparse data. In this paper, we propose a CNN model based on sparse tensors for efficient processing of high-resolution shapes represented as binary voxel occupancy grids....
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| Hauptverfasser: | , , , , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
Nature Portfolio
2023-11-01
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| Schriftenreihe: | Scientific Reports |
| Online-Zugang: | https://doi.org/10.1038/s41598-023-47437-6 |
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