Attention U-Net: Learning Where to Look for the Pancreas论文笔记
attention u-net论文翻译笔记 摘要 [外链图片 我们提出了一种新颖的医学图像注意力们模型，它能自动学习聚焦在形状、尺寸变化的目标结构。用AG训练的模型隐形地抑制输入图像的非相关区域，同时强调对指定任务有用的显著性特征。这让我们不必去显式地使用级联CNN的组织定位模块。AG可以轻易的被集成到标准的CNN结构中，比如U-net模型，带有少量的计算开销同时能增加模型的敏感性和准确性。提出的
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相关文章
- 1. Attention U-Net: Learning Where to Look for the Pancreas
- 2. 论文阅读——Attention U-Net: Learning Where to Look for the Pancreas
- 3. 浅谈Attention UNet
- 4. Tell Me Where to Look: Guided Attention Inference Network
- 5. GAIN论文解读 Tell Me Where to Look: Guided Attention Inference Network
- 6. Hierarchical combinatorial deep learning architecture for pancreas segmentation-笔记
- 7. 论文笔记：Learning to See in the Dark
- 8. 论文笔记：Knowing When to Look: Adaptive Attention via A Visual Sentinel for Image Captioning
- 9. Learning to Paraphrase for Question Answering 论文笔记
- 10. 1606.End--to-End Comparative Attention Networks for Person Re-identification 论文笔记