Illustration of UNet++ from Zhou et al. (2019). The X^i·j are the same convolutional layers as for UNet. The difference between UNet and UNet++ can be depicted in three main points: 1) convolution layers on skip pathways (in green), which reduces the semantic gap between encoder and decoder feature maps; 2) dense skip connections on skip pathways (in blue), which improves the gradient flow; and 3) deep supervision (in red), which enables model pruning (Lee et al. 2015).