語義分割論文翻譯：Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network
1、Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network 摘要：小的卷積核堆疊比用一個大的卷積覈計算更加高效。在語義分割領域，需要執行每個像素的預測分類，更大的卷積核（感受野更大），對於分類和定位任務來說，作用更大。所以提出GCN來解決語義分割的分類和定位的問題。文中還提出一個基於
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- 1. 語義分割--Large Kernel Matters--Improve Semantic Segmentation by Global Convolutional Network
- 2. 語義分割之Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network
- 3. 圖像分割：GCN: Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network
- 4. Large Kernel Matters ——Improve Semantic Segmentation by Global Convolutional Network論文筆記
- 5. 【論文學習記錄】Large Kernel Matters-Improve Semantic Segmentation by Global Convolutional Network
- 6. Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network論文閱讀
- 7. Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network------論文理解
- 8. PaperReading4-Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network
- 9. Semantic Segmentation---GCN:Large Kernel Matters---Improve Semantic Segmantic by Global ...（論文解讀四）
- 10. 【圖像語義分割】Large Kernel Maters--Improved Semantic Segmentation by Global ConvNet