Context: At the core of deep learning’s success is a model known as a convolutional neural network (CNN). A CNN typically works by extracting features from images and then feeding those features into a fully connected neural network to generate a prediction. The feature extraction layers play a crucial role in reducing the number of features from an extensive array of individual pixel values to a smaller, meaningful feature set that aids in label prediction. Since CNNs consist of multiple layers, each serves a specific function in feature extraction or label prediction. Question: Which of the following are valid layer types in a CNN? (Select five)