Schematic of the TernausNet architecture and the transformations performed on the input image (left). Yellow blocks represent convolutions and transpose convolutions, while red and blue blocks depict max-pooling and unpooling, respectively. The arrows from the encoder (first half) to the decoder (second half) show skip connections, which connect non-adjacent layers and enhance the performance of the network. The thickness of the blocks is proportional to the number of channels after the transformation; the input image has three (RGB) and the sigmoid output has one. The height of the blocks relates to the relative map size after the transformation. Adapted from Iglovikov & Shvets (2018).