TABLE I:

The network architecture of the Tiramisu segmentation engine.

Layers applied	# of feature maps
Input	1
3 × 3 Convolution	48
Dense Block (4 layers) + Transition Down	112
Dense Block (5 layers) + Transition Down	192
Dense Block (7 layers) + Transition Down	304
Dense Block (10 layers) + Transition Down	464
Dense Block (12 layers) + Transition Down	656
Dense Block (15 layers)	896
Transition Up + Dense Block (12 layers)	1088
Transition Up + Dense Block (10 layers)	816
Transition Up + Dense Block (7 layers)	578
Transition Up + Dense Block (5 layers)	384
Transition Up + Dense Block (4 layers)	256
1 × 1 Convolution	2
Softmax	2