Context: please provide short answer of following question
Question: How do convolutional and pooling layers work together in CNNs?
Answer: In CNNs, convolutional layers extract features from the input images by applying filters that detect edges, textures, and other patterns. Pooling layers then downsample the resulting feature maps, reducing their spatial dimensions while retaining the most important information. This combination allows the CNN to learn hierarchical representations of the input data, enabling it to capture both low-level details and high-level features.