Fig. 3
From: DCATNet: polyp segmentation with deformable convolution and contextual-aware attention network
Contextual Attention Gate Module structure. The CAG module fuses high-level and low-level features through a context-aware attention mechanism. High-level and low-level features are first processed with \(1 \times 1\) convolutions, then concatenated. The sigmoid function generates a weight map to re-weight the features. The final output is generated by element-wise addition