How do attention mechanisms integrate with CNN architectures?

Attention mechanisms enhance CNNs by dynamically weighting spatial or channel features based on importance.

Traditional CNNs treat all spatial regions equally after convolution. Attention mechanisms introduce adaptive weighting so the model focuses on important regions or channels. Spatial attention highlights important regions in the image, while channel attention emphasizes informative feature maps. This improves performance in tasks like classification and segmentation.