diff --git a/mlair/model_modules/convolutional_networks.py b/mlair/model_modules/convolutional_networks.py
index 5146fe529ef01aabc2440581198d37d0d2ab6a4b..2d8fd9e2fe4292ef7989d932d9b7d4fc9fbe756d 100644
--- a/mlair/model_modules/convolutional_networks.py
+++ b/mlair/model_modules/convolutional_networks.py
@@ -83,17 +83,15 @@ class CNN(AbstractModelClass):
         """
         x_input = keras.layers.Input(shape=self._input_shape)
         kernel = (self.kernel_size, 1)
-        pad_size = PadUtils.get_padding_for_same(kernel)
-        x_in = Padding2D("SymPad2D")(padding=pad_size, name="SymPad1")(x_input)
         x_in = keras.layers.Conv2D(filters=16, kernel_size=kernel,
                                    kernel_initializer=self.kernel_initializer,
-                                   kernel_regularizer=self.kernel_regularizer)(x_in)
+                                   kernel_regularizer=self.kernel_regularizer)(x_input)
         x_in = self.activation()(x_in)
         x_in = keras.layers.Conv2D(filters=32, kernel_size=kernel,
                                    kernel_initializer=self.kernel_initializer,
                                    kernel_regularizer=self.kernel_regularizer)(x_in)
-        x_in = keras.layers.MaxPooling2D(kernel, strides=(1, 1), padding='valid')(x_in)
         x_in = self.activation()(x_in)
+        x_in = keras.layers.MaxPooling2D(kernel, strides=(1, 1), padding='valid')(x_in)
         x_in = keras.layers.Conv2D(filters=64, kernel_size=kernel,
                                    kernel_initializer=self.kernel_initializer,
                                    kernel_regularizer=self.kernel_regularizer)(x_in)