**Number of filters**: The number of convolutional filters to include in the layer

**Width of filter**: The width of the weight matrix of a single filter

**Height of filter**: The width of the weight matrix of a single filter

**Horizontal stride**: The number of pixels to move while performing the convolution along the horizontal axis.

**Vertical stride**: Default: The number of pixels to move while performing the convolution along the vertical axis.

**Activation**: The function that will applied to each element of the output.

**Padding**: Same (output (height) x (width) is the same as the input) or valid (output (height) x (width) is smaller than the input)

**Trainable**: whether we want the training algorithm to change the value of the weights during training.