Road Extraction by Deep Residual U-Net

时间 2021-01-12

标签语义分割论文笔记繁體版

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Abstract U-Net与residual单元结合的优势：（1）residual units可以简化深层网络的训练（2）大量的skip connections促进了信息的传播，可以设计出参数更好性能更好的网络。 1.INTRODUCTION 道路提取：道路面积的提取和道路中心线的提取道路面积提取前人工作：（1）shape index特征 + SVM【11】（2）使用概率SVM设计多级

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1. Fully Convolutional Network for Automatic Road Extraction from Satellite Imagery
2. LiDAR Textbook & Automated Road Network Extraction
3. Stacked U-Nets with Multi-Output for Road Extraction
4. Deep Residual Learning for Image Recognition
5. How does deep residual learning work?
6. ResNet--Deep Residual Learning for Image Recognition
7. Deep Residual Learning for Image Recognition （zh）
8. [ResNet]Deep Residual Learning for Image Recognition
9. 论文笔记：Deep Residual Learning
10. 【论文】Deep Pyramidal Residual Networks（译）

>>更多相关文章<<