diff --git a/modules/deeplearning/icing_cnn.py b/modules/deeplearning/icing_cnn.py
index 037d4cd6e506e36187b4ed02caa00e3128ab1fb1..c1620f4dd643a47a66d3f32b966e9132a109e9d5 100644
--- a/modules/deeplearning/icing_cnn.py
+++ b/modules/deeplearning/icing_cnn.py
@@ -550,21 +550,21 @@ class IcingIntensityNN:
 
         fac = 2
 
-        fc = build_residual_block(flat, drop_rate, fac*n_hidden, activation, 'Residual_Block_1', doBatchNorm=True)
+        fc = build_residual_block(flat, drop_rate, fac*n_hidden, activation, 'Residual_Block_1', doDropout=True, doBatchNorm=True)
 
-        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_2', doBatchNorm=True)
+        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_2', doDropout=True, doBatchNorm=True)
 
-        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_3', doBatchNorm=True)
+        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_3', doDropout=True, doBatchNorm=True)
 
-        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_4', doBatchNorm=True)
+        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_4', doDropout=True, doBatchNorm=True)
 
-        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_5', doBatchNorm=True)
+        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_5', doDropout=True, doBatchNorm=True)
 
-        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_6', doBatchNorm=True)
+        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_6', doDropout=True, doBatchNorm=True)
 
-        # fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_7', doBatchNorm=True)
+        # fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_7', doDropout=True, doBatchNorm=True)
         #
-        # fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_8', doBatchNorm=True)
+        # fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_8', doDropout=True, doBatchNorm=True)
 
         fc = tf.keras.layers.Dense(n_hidden, activation=activation)(fc)
         fc = tf.keras.layers.BatchNormalization()(fc)