Question - What are the various layers present in a CNN?
Answer -
There are four main layers that form a convolutional neural network:
- Convolution: These are layers consisting of entities called filters that are used as parameters to train the network.
- ReLu: It is used as the activation function and is always used with the convolution layer.
- Pooling: Pooling is the concept of shrinking the complex data entities that form after convolution and is primarily used to maintain the size of an image after shrinkage.
- Connectedness: This is used to ensure that all of the layers in the neural network are fully connected and activation can be computed using the bias easily.