DenseNet: Densely connected convolutional network
貢獻和總結 1. 使用dense block(3到4個左右), 每個dense裏面的每一層和其餘任意層都連接, 前面的作爲輸入, 輸出到之後所有的. 2. 1X1卷積可以用來改變每一層的輸入層數 1 introduction 設計靈感來自DCNN中信息在長距離傳輸中可能會丟失. dense block 結構是每一層都很其餘的層連接: 當前層的輸入串聯之前所有層的輸出特徵圖, 然後輸出特徵圖串聯
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- 1. DenseNet--Densely Connected Convolutional Networks
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- 6. DenseNet---《Densely Connected Convolutional Networks》
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相關文章
- 1. DenseNet--Densely Connected Convolutional Networks
- 2. 【DenseNet】《Densely Connected Convolutional Networks》
- 3. DenseNet Densely Connected Convolutional Networks
- 4. DenseNet——Densely Connected Convolutional Networks
- 5. Densely Connected Convolutional Networks(DenseNet)
- 6. DenseNet---《Densely Connected Convolutional Networks》
- 7. Densely Connected Convolutional Networks (DenseNet 2017 CVPR)
- 8. Ensemble of 3D densely connected convolutional network
- 9. Densely Connected Convolutional Networks
- 10. Densely Connected Convolutional Networks(2017)