Fig. 2.

The proposed Cancer-Net SCa network architectures. The number in each convolution module represents the number of channels. The numbers in each visual attention condenser represents the number of channels for the down-mixing layer, the embedding structure, and the up-mixing layer, respectively (details can be found in [15]). It can be observed that all Cancer-Net SCa architectures exhibit both great macroarchitecture and microarchitecture design diversity, with certain models exhibiting specific lightweight macroarchitecture design characteristics such as attention condenser and projection–expansion–projection–expansion (PEPE) design patterns comprised of channel dimensionality reduction, depthwise convolutions, and pointwise convolutions