Fig. 5:

(a) General architecture of the Tiramisu [17] is illustrated. The architecture is composed of downsampling and upsampling paths including Convolution, Dense Block, Concatenation (C), Skip Connection (dashed lines), Transition Down, and Transition Up layers. Concatenation layer appends the input of the dense block layer to the output of it. Skip connection copies the concatenated feature maps to the upsampling path. (b) A sample dense block with 4 layers is shown to its connections. With a growth rate of k, each layer in dense block appends k feature maps to the input. Hence, the output contains 4 × k features maps.