Practical Convolutional Neural Networks

Convolutional layers in Keras

To create a convolutional layer in Keras, you must first import the required modules as follows:

from keras.layers import Conv2D

Then, you can create a convolutional layer by using the following format:

Conv2D(filters, kernel_size, strides, padding, activation='relu', input_shape)

You must pass the following arguments:

• filters: The number of filters.
• kernel_size: A number specifying both the height and width of the (square) convolution window. There are also some additional optional arguments that you might like to tune.
• strides: The stride of the convolution. If you don't specify anything, this is set to one.
• padding: This is either valid or same. If you don't specify anything, the padding is set to valid