Richer Convolutional Features for Edge Detection论文笔记
总结 使用CNN进行边缘检测，主要在数据库BSD500实验。主要贡献如下： 网络开始阶段，细节边缘丰富。网络后续阶段，细节（内部）边缘减少，轮廓信息更明显。所以利用FPN思想结合高层和底层的Feature Map进行边缘检测。 优化LOSS FUNCTION，使其更具有一般性。 在BSDS500 benchmark，得到 ODS F-measure 0.811 (8FPS) 简化版本ODS F-m
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相关文章
- 1. Richer Convolutional Features for Edge Detection 论文阅读
- 2. Richer Convolutional Features for Edge Detection（RCF论文学习笔记）
- 3. Richer Convolutional Features for Edge Detection(RCF)阅读笔记
- 4. CNN边缘检测--Richer Convolutional Features for Edge Detection
- 5. 论文见解之RCF：Richer Convolutional Features for Edge Detection
- 6. 论文笔记：Learning Region Features for Object Detection
- 7. 论文阅读《Edge Detection Using Convolutional Neural Network》
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- 9. 论文笔记 - Cross-dimensionalWeighting for Aggregated Deep Convolutional Features
- 10. False Positive Reduction Using Multiscale Contextual Features for Prostate Cancer Detection..论文笔记