Retinal Vessel Segmentation by Deep Residual Learning with Wide Activation

Figure 2

Schematic of WDSR-A. Identity represents the identity mapping layer, Add denotes the element-wise summation over channels. In the dashed box, Conv stands for convolution, ReLU indicates the activation layer, C is the abbreviation of the channel, and the two conical shapes are the convolution layers that expand and slim the channel, respectively. The principle of wide activation is expanding features before the activation layer without increasing computation. A further explanation is shown in Figure 3.