In the context of CNNs, what does a stride of 3 indicate?

A stride of 3 in the context of Convolutional Neural Networks (CNNs) indicates that the filter moves across the image in 3-pixel intervals. This means that after applying the filter to a specific region of the input image, the filter shifts to the right by 3 pixels (or down by 3 pixels when moving between rows). This setting affects the spatial dimensions of the output feature map, making it smaller compared to using a stride of 1, where the filter would move one pixel at a time.

By increasing the stride, the CNN reduces the amount of overlapping information captured between the output feature maps. This can help in capturing more abstract features while also reducing the computational load, but it may also lead to a loss of detail since fewer regions of the input image are processed. Hence, option B accurately describes the behavior of the filter with a stride of 3.