diff --git a/params/iri_ground_segmentation.yaml b/params/iri_ground_segmentation.yaml
index d70c1265058182369b61b554499b80dd1da5b535..f0e1eb8d5ae3563c685aee4da4991a451d06ef13 100644
--- a/params/iri_ground_segmentation.yaml
+++ b/params/iri_ground_segmentation.yaml
@@ -36,13 +36,13 @@ iri_ground_segmentation: {
                                     ## and a big value will increase the number of false ground points)
 
   # Neural Network related parameters
-  use_neural_network: true,
+  use_neural_network: false,
   extract_data_to_external_training_of_the_network: false,
   dataset_filename_with_global_path: '/home/idelpino/Documentos/dataset_rgb_hsv_olbp_10_frame_inc.csv',
-  neural_net_filename_with_global_path: '/media/sf_virtual_box_shared/neural_networks/five_classes_13_features_39_neurons.csv',
+  neural_net_filename_with_global_path: '/media/sf_virtual_box_shared/neural_networks/veg_terrain_and_obs_13_features_39_neurons.csv',
   neural_net_number_of_features: 13,
   neural_net_number_of_neurons_in_hidden_layer: 39,
-  neural_net_number_of_neurons_in_output_layer: 5,
+  neural_net_number_of_neurons_in_output_layer: 2,
   
   # labeling parameters
   max_pred_std_dev_for_labelling: 0.5,                   ## ONLY IN USE TO GIVE COLOUR TO DENSE RECONSTRUCTION
@@ -53,6 +53,6 @@ iri_ground_segmentation: {
                                                          
   # visualization and debug parameters
   measure_performance: false,            ## (feature still not debugged) Flag to measure number of execution and execution times of the different functions of the algorithm 
-  show_dense_reconstruction: false,      ## To show a dense ground surface reconstruction using the predictions of the ground mode (colored using the std_dev of z coordinate)   
+  show_dense_reconstruction: true,      ## To show a dense ground surface reconstruction using the predictions of the ground mode (colored using the std_dev of z coordinate)   
                                          ## or alternatively the "elevation point cloud" (useful for parameter tunning) 
 }
diff --git a/src/ground_segmentation_alg_node.cpp b/src/ground_segmentation_alg_node.cpp
index a79fb569f59ab8515d094a77726d126f6f86c2cd..6c217f0acc7e37a98c5cd62cfdcaf2e61200f62c 100644
--- a/src/ground_segmentation_alg_node.cpp
+++ b/src/ground_segmentation_alg_node.cpp
@@ -577,6 +577,7 @@ void GroundSegmentationAlgNode::node_config_update(Config &config, uint32_t leve
       config.extract_data_to_external_training_of_the_network;
 
   // labeling parameters
+  this->alg_.filtering_configuration_.score_threshold = config_.score_threshold;
   this->alg_.filtering_configuration_.max_pred_std_dev_for_labelling = config.max_pred_std_dev_for_labelling;
   this->alg_.filtering_configuration_.classify_not_labeled_points_as_obstacles =
       config_.classify_not_labeled_points_as_obstacles;
@@ -620,6 +621,9 @@ void GroundSegmentationAlgNode::node_config_update(Config &config, uint32_t leve
   std::cout << "mahalanobis_threshold       =                   "
       << this->alg_.filtering_configuration_.mahalanobis_threshold << std::endl;
 
+  std::cout << "score_threshold       =                   "
+      << this->alg_.filtering_configuration_.score_threshold << std::endl;
+
   std::cout << "use_neural_network       =                   "
       << this->alg_.filtering_configuration_.use_neural_network << std::endl;