Large Kernel Matters—— Improve Semantic Segmentation by Global Convolutional Network------論文理解
參考博客：http://www.javashuo.com/article/p-dlhvytpa-sx.html 1. 概述 目前網絡架構設計的趨勢均是在相同計算量的前提下將大的卷積核替換爲多個小的卷積核（如1x1和3x3）堆疊而成 。但在語義分割中需要同時進行分類和定位的時候大的卷積核佔很重要的角色。爲解決分類和定位問題，我們提出了GCN網絡。同時提出了基於殘差的邊界修正，來更好細化物體邊界。 語
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相關文章
- 1. Large Kernel Matters ——Improve Semantic Segmentation by Global Convolutional Network論文筆記
- 2. 【論文學習記錄】Large Kernel Matters-Improve Semantic Segmentation by Global Convolutional Network
- 3. Large Kernel Matters —— Improve Semantic Segmentation by Global Convolutional Network論文閱讀
- 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. Large Kernel Matters論文理解
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