基础学习:(5)不同卷积
文章目录
- 基础学习:(5)不同卷积
- 前言
- 1 deconvlution == transposed convolution
- 2 对比
- 2.1 Convolution animations
- 2.2 Transposed convolution animations
- 2.3 Dilated convolution
前言
本文言简意赅的说明了反卷积(deconvlution),卷积(convolution),转置卷积(transposed convolution),空洞卷积(dilated convolution)的区别
1 deconvlution == transposed convolution
之前人觉得叫deconvolution 不够严谨,所以改成了叫 transposed convolution
deconv 就是 还原尺寸,其他没啥。
Vincent Dumoulin, Francesco Visin - A guide to convolution arithmetic for deep learning (BibTeX)
2 对比
这里我看到网上github 上讲的最好,有时候打开github 比较慢,我这里复制了下来
链接:https://github.com/vdumoulin/conv_arithmetic/tree/master
2.1 Convolution animations
N.B.: Blue maps are inputs, and cyan maps are outputs.
no padding, no strides | Arbitrary padding, no strides | Half padding, no strides | Full padding, no strides | No padding, strides | Padding, strides | Padding, strides (odd) |
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2.2 Transposed convolution animations
N.B.: Blue maps are inputs, and cyan maps are outputs.
no padding, no strides, transposed | Arbitrary padding, no strides, transposed | Half padding, no strides, transposed | Full padding, no strides, transposed | No padding, strides, transposed | Padding, strides, transposed | Padding, strides (odd), transposed |
---|---|---|---|---|---|---|
2.3 Dilated convolution
N.B.: Blue maps are inputs, and cyan maps are outputs.
No padding, no stride, dilation |
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