論文筆記：Densely Connected Convolutional Networks
Dense Block: 每一層只增加 k = 4 個feature map 然後跟前面的所有concat，再 BN-->ReLU-->Conv （一般k = 12） 整體結構： Dense Block之間是Conv和Pooling Bottleneck layers: 儘管每次只增加k個，但是到後來還是很大，所以,採用Bottleneck，即BN-ReLU-Conv變成 BN-ReL
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相關文章
- 1. 論文筆記Densely Connected Convolutional Networks v1
- 2. 【論文閱讀筆記】Densely Connected Convolutional Networks
- 3. 論文筆記——Densely Connected Convolutional Networks(DenseNet)
- 4. Densely Connected Convolutional Networks 論文筆記
- 5. Densely Connected Convolutional Networks
- 6. 【論文】Densely Connected Convolutional Networks（DenseNet譯文）
- 7. DenseNet--Densely Connected Convolutional Networks
- 8. Densely Connected Convolutional Networks(2017)
- 9. DenseNet——Densely Connected Convolutional Networks
- 10. Densely Connected Convolutional Networks(DenseNet)