C1_W3 - Convolution

Hello!
I have a question, could you help me?
Considering the code below:
"
model = tf.keras.models.Sequential([
tf.keras.layers.Conv2D(32, (3,3), activation=‘relu’, input_shape=(28,28,1)),
tf.keras.layers.MaxPooling2D(2,2),

     tf.keras.layers.Flatten(),
     tf.keras.layers.Dense(128, activation='relu'),
     tf.keras.layers.Dense(10, activation='softmax')
 ])

"

  • I can say that the command “tf.keras.layers.Conv2D(32, (3,3), activation=‘relu’, input_shape=(28,28,1)),” creates 32 feature matrices and then reduces each one in half with the command “tf.keras.layers.MaxPooling2D(2,2),”?

Best regards