【图像语义分割】Fully Convolutional Networks for Semantic Segmentation
FCN这篇文章是第一次用CNN的方式端对端（end-to-end）的解决了图像语义分割问题，在Semantic Segment这个领域中也算划时代的论文了 不同于常规的classification network, Sementic Segment侧重于像素级的分类。本文通过对常规classification network（Alexnet, VGG, GoogLeNet）进行fine-tunin
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相关文章
- 1. 语义分割--Fully Convolutional DenseNets for Semantic Segmentation
- 2. 深度图像分割 -- Fully Convolutional Networks for Semantic Segmentation
- 3. 深度学习之图像分割 《Fully Convolutional Networks for Semantic Segmentation》—FCN
- 4. FCN—— Fully Convolutional Networks for Semantic Segmentation
- 5. Fully Convolutional Adaptation Networks for Semantic Segmentation
- 6. Fully Convolutional Networks for Semantic Segmentation
- 7. FCN-Fully Convolutional Networks for Semantic Segmentation
- 8. 图像分割“Fully Convolutional Instance-aware Semantic Segmentation”
- 9. 图像分割“The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation”
- 10. 语义分割--Global Deconvolutional Networks for Semantic Segmentation