Fig. 2
From: Comparison of automated segmentation techniques for magnetic resonance images of the prostate
Architecture of the EfficientNetB0 backbone used in our transfer learning model. Blue and red blocks represent mobile inverted bottleneck convolution (MBConv) blocks (see Fig. 3), with a kernel size of 3x3 and 5x5, respectively. The light gray block represents a strided convolution followed by batch norm and a swish activation, while the dark gray block represents an MBConv block with expansion factor 1 and kernel size 3. The resolution at each level is displayed in bold and the number of filters (output channels) is displayed with the ‘f’ suffix