Retinal Vessel Segmentation by Deep Residual Learning with Wide Activation

Figure 3

Principle of wide activation [25]. and , stand for channels, r is the expansion factor, and k × k below Conv is the kernel size. In deep learning, the width refers to the number of channels. Wide activation focuses on the width (the C parameter) to improve feature utilization.

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