Basics of Convolutional Neural Networks — Stride and Pooling

Stride

The stride is how the convolution filter is moved over the original image. The filter is moved across the image left to right, top to bottom, with a one-pixel column change on the horizontal movements, then a one-pixel row change on the vertical movements. By changing the stride, we could move our filter by the size of pixels each time, resulting in a smaller number of possible locations for the filter. The default stride in two dimensions is (1,1) for the height and the width movement and it works well in most cases.

Pooling

A pooling layer is a new layer added after the convolutional layer. Specifically, after a nonlinearity has been applied to the feature maps output by a convolutional layer. Pooling involves selecting a pooling operation. Two common functions used in the pooling operation are average pooling and max pooling.

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Kinder Chen

Kinder Chen

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