Deconvolution
Visualizing and Understanding Convolutional Networks于2014年发表于ECCV。该文章是第一篇提出可视化卷积神经网络的文章。使用Deconvolution技术（Zeiler et al., 2011）重建源图中对某类起重要作用的区域。 Deconvolution 反卷积顾名思义与卷积操作和传播方向正好相反，对卷积操作做如下修改： 卷积层：使用转置
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相关文章
- 1. Compressive Blind Deconvolution Formula
- 2. CNN unpooling和deconvolution
- 3. Deconvolution/Transposed convolution
- 4. 反卷积 deconvolution
- 5. Convolution Networks 和Deconvolution Networks
- 6. UpPooling/UpSampling/Deconvolution/Transposed convolution
- 7. 图解deconvolution(transpose convolution)
- 8. Deconvolution与Upsampling的区别
- 9. Deconvolution、upsampling和unpooling详解
- 10. Learning Deconvolution Network for Semantic Segmentation