【圖像語義分割】Fully Convolutional Networks for Semantic Segmentation
FCN這篇文章是第一次用CNN的方式端對端（end-to-end）的解決了圖像語義分割問題，在Semantic Segment這個領域中也算劃時代的論文了 不同於常規的classification network, Sementic Segment側重於像素級的分類。本文通過對常規classification network（Alexnet, VGG, GoogLeNet）進行fine-tunin
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- 1. 語義分割--Fully Convolutional DenseNets for Semantic Segmentation
- 2. 深度圖像分割 -- Fully Convolutional Networks for Semantic Segmentation
- 3. 深度學習之圖像分割 《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. 圖像分割「Fully Convolutional Instance-aware Semantic Segmentation」
- 9. 圖像分割「The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation」
- 10. 語義分割--Global Deconvolutional Networks for Semantic Segmentation
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相關文章
- 1. 語義分割--Fully Convolutional DenseNets for Semantic Segmentation
- 2. 深度圖像分割 -- Fully Convolutional Networks for Semantic Segmentation
- 3. 深度學習之圖像分割 《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. 圖像分割「Fully Convolutional Instance-aware Semantic Segmentation」
- 9. 圖像分割「The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation」
- 10. 語義分割--Global Deconvolutional Networks for Semantic Segmentation