Figure 8.

Comparison of different hierarchical architectures for classification models

After patch embedding, the feature map size is $h\times w\times c$, where h, w, and c are the height, width, and channel numbers. There is a patch merging operation between every two stages, usually $2\times 2$ patches are merged, and the number of channels doubles. The resolutions of the feature maps are different, usually $h=H/16$ in single stage, $h=H/7$ in two stage, and $h=H/4$ in pyramid, where H and W are the height and width of the input image.