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The fully convolutional network with a output stride of 8 (FCN-8s) architecture. The network consists of 15 convolutional layers and 5 max pooling layers. The outputs from pooling layers three and four were routed through deconvolution layers to help restore smaller details in the segmented images. (This figure is redrawn from Long et al. [17]).
