Fig. 4
From: DCATNet: polyp segmentation with deformable convolution and contextual-aware attention network
The multi-scale feature extraction module consists of an encoder and decoder, each built with standard convolutional blocks, batch normalization, and ReLU activation. The final stage of the encoder uses dilation = 2 to capture global information