Convolutions

Depthwise Separable Convolution

Introduced by Chollet in Xception: Deep Learning With Depthwise Separable Convolutions

While standard convolution performs the channelwise and spatial-wise computation in one step, Depthwise Separable Convolution splits the computation into two steps: depthwise convolution applies a single convolutional filter per each input channel and pointwise convolution is used to create a linear combination of the output of the depthwise convolution. The comparison of standard convolution and depthwise separable convolution is shown to the right.

Credit: Depthwise Convolution Is All You Need for Learning Multiple Visual Domains

Source: Xception: Deep Learning With Depthwise Separable Convolutions

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