『 论文阅读』U-Net Convolutional Networks for Biomedical Image Segmentation
U-Net Convolutional Networks for Biomedical Image Segmentation 用于生物医学图像分割的U-Net卷积网络 Abstract 普遍认为，深度网络的成功培训需要数千个带注释的训练样本。在本文中，提出了一种网络和培训策略，依靠强大的数据增强功能（data augmentation）更有效地使用可用的注释示例。该体系结构包括捕捉上下文的收缩路径
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- 9. Paper | U-Net: Convolutional Networks for Biomedical Image Segmentation
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相关文章
- 1. U-Net: Convolutional Networks for Biomedical Image Segmentation------2015CVPR UNet论文解读
- 2. 《U-Net: Convolutional Networks for Biomedical Image Segmentation》论文阅读
- 3. [论文阅读笔记]U-Net: Convolutional Networks for Biomedical Image Segmentation
- 4. [U-Net]Convolutional Networks for Biomedical Image Segmentation
- 5. [U-Net] U-Net: Convolutional Networks for Biomedical Image Segmentation
- 6. U-Net: Convolutional Networks for Biomedical Image Segmentation
- 7. 论文精读及分析：U-Net: Convolutional Networks for Biomedical Image Segmentation
- 8. 【Semantic Segmentation】U-Net: Convolutional Networks for Biomedical Image Segmentation 论文解析(转)...
- 9. Paper | U-Net: Convolutional Networks for Biomedical Image Segmentation
- 10. U-Net: Convolutional Networks for Biomedical Image Segmentation翻译