3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation 论文解读与程序复现
转载请注明出处：https://blog.csdn.net/wyzjack47/article/details/81118483 这篇论文题为3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation。 论文解读 在生物医学领域，3D数据是很多的，一层一层转化为2D数据去标注训是不现实的，而且用整个3D体积的全部数
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相关文章
- 1. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
- 2. 论文关键点分析：3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
- 3. 论文阅读笔记（四十八）：3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
- 4. LEARNING VOLUMETRIC SEGMENTATION FOR LUNG TUMOR
- 5. [论文解读] DSD -- Dense-Sparse-Dense Training for Neural Network
- 6. 【论文精读】3D Shape Segmentation
- 7. [论文解读+复现] PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
- 8. 《Unet》论文阅读与
- 9. 论文阅读笔记（五十四）：V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
- 10. Ground Segmentation based on Loopy Belief Propagation for Sparse 3D Point Clouds （论文速读）