【論文學習記錄】Large Kernel Matters-Improve Semantic Segmentation by Global Convolutional Network
這篇文章是收錄在CVPR 2017上的文章，作者來自清華大學和曠視科技。論文原文《Large Kernel Matters-Improve Semantic Segmentation by Global Convolutional Network》。 語義分割可以看成是一個逐像素的分類任務，同時包含分類和定位。對於分類任務，模型必須是具有不變性的，但是對於定位任務，模型應該是對變換敏感的。 爲應對
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- 3. Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network------論文理解
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- 8. Semantic Segmentation---GCN:Large Kernel Matters---Improve Semantic Segmantic by Global ...（論文解讀四）
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相關文章
- 1. Large Kernel Matters ——Improve Semantic Segmentation by Global Convolutional Network論文筆記
- 2. Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network論文閱讀
- 3. Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network------論文理解
- 4. 語義分割--Large Kernel Matters--Improve Semantic Segmentation by Global Convolutional Network
- 5. PaperReading4-Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network
- 6. 語義分割之Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network
- 7. 圖像分割：GCN: Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network
- 8. Semantic Segmentation---GCN:Large Kernel Matters---Improve Semantic Segmantic by Global ...（論文解讀四）
- 9. 【圖像語義分割】Large Kernel Maters--Improved Semantic Segmentation by Global ConvNet
- 10. GCN_large kernel matters_improving semantic seg by global conv network