Strides

In convolutional neural networks, a stride determines how many pixels the filter (or kernel) shifts horizontally and vertically during the convolution operation. A stride of 1 means the filter moves one pixel at a time, resulting in a more detailed feature map. A larger stride, like 2 or 3, causes the filter to jump over pixels, producing a smaller feature map and reducing computational cost, but potentially missing finer details in the input image.

Visit the following resources to learn more:

• @article@Padding and Stride
• @video@Convolution padding and stride