diff --git a/bob/learn/tensorflow/loss/ContrastiveLoss.py b/bob/learn/tensorflow/loss/ContrastiveLoss.py
index f72cbd8ae2312cdf39e5e4a3c9d375ac833318fc..edf6c09e7faf1054fea2b00ca15aad3b5ea73ef1 100644
--- a/bob/learn/tensorflow/loss/ContrastiveLoss.py
+++ b/bob/learn/tensorflow/loss/ContrastiveLoss.py
@@ -52,19 +52,28 @@ def contrastive_loss(left_embedding,
             within_class = tf.multiply(one - labels,
                                        tf.square(d))  # (1-Y)*(d^2)
             within_class_loss = tf.reduce_mean(
-                within_class, name=tf.GraphKeys.LOSSES)
+                within_class, name="within_class")
+            tf.add_to_collection(tf.GraphKeys.LOSSES, within_class_loss)
 
         with tf.name_scope("between_class"):
             max_part = tf.square(tf.maximum(contrastive_margin - d, 0))
             between_class = tf.multiply(
                 labels, max_part)  # (Y) * max((margin - d)^2, 0)
             between_class_loss = tf.reduce_mean(
-                between_class, name=tf.GraphKeys.LOSSES)
+                between_class, name="between_class")
+            tf.add_to_collection(tf.GraphKeys.LOSSES, between_class_loss)
 
         with tf.name_scope("total_loss"):
             loss = 0.5 * (within_class + between_class)
-            loss = tf.reduce_mean(loss, name=tf.GraphKeys.LOSSES)
-
+            loss = tf.reduce_mean(loss, name="total_loss_raw")
+            tf.summary.scalar('loss_raw', loss)
+            tf.add_to_collection(tf.GraphKeys.LOSSES, loss)
+            
+            ## Appending the regularization loss
+            #regularization_losses = tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES)
+            #loss = tf.add_n([loss] + regularization_losses, name="total_loss")
+            
+            
         tf.summary.scalar('loss', loss)
         tf.summary.scalar('between_class', between_class_loss)
         tf.summary.scalar('within_class', within_class_loss)
diff --git a/bob/learn/tensorflow/loss/TripletLoss.py b/bob/learn/tensorflow/loss/TripletLoss.py
index fe59cbb96fdd1050d4f94c99205b9bfdf0c69b48..8aa07924a4360b725e2887059b790f8bfd1f2f29 100644
--- a/bob/learn/tensorflow/loss/TripletLoss.py
+++ b/bob/learn/tensorflow/loss/TripletLoss.py
@@ -53,14 +53,28 @@ def triplet_loss(anchor_embedding,
             tf.square(tf.subtract(anchor_embedding, negative_embedding)), 1)
 
         basic_loss = tf.add(tf.subtract(d_positive, d_negative), margin)
-        loss = tf.reduce_mean(
-            tf.maximum(basic_loss, 0.0), 0, name=tf.GraphKeys.LOSSES)
-        between_class_loss = tf.reduce_mean(d_negative)
-        within_class_loss = tf.reduce_mean(d_positive)
 
-        tf.summary.scalar('loss', loss)
-        tf.summary.scalar('between_class', between_class_loss)
-        tf.summary.scalar('within_class', within_class_loss)
+        with tf.name_scope("TripletLoss"):
+            # Between
+            between_class_loss = tf.reduce_mean(d_negative)
+            tf.summary.scalar('between_class', between_class_loss)            
+            tf.add_to_collection(tf.GraphKeys.LOSSES, between_class_loss)
+        
+            # Within
+            within_class_loss = tf.reduce_mean(d_positive)
+            tf.summary.scalar('within_class', within_class_loss)            
+            tf.add_to_collection(tf.GraphKeys.LOSSES, within_class_loss)
+
+            # Total loss
+            loss = tf.reduce_mean(
+                tf.maximum(basic_loss, 0.0), 0, name="total_loss")
+            tf.add_to_collection(tf.GraphKeys.LOSSES, loss)
+            tf.summary.scalar('loss_raw', loss)            
+
+            # Appending the regularization loss
+            #regularization_losses = tf.get_collection(tf.GraphKeys.REGULARIZATION_LOSSES)
+            #loss = tf.add_n([loss] + regularization_losses, name="total_loss")
+            #tf.summary.scalar('loss', loss)
 
         return loss
 
diff --git a/bob/learn/tensorflow/network/InceptionResnetV2.py b/bob/learn/tensorflow/network/InceptionResnetV2.py
index b52fcc48c2a3638fb80b5e86a7c061243f08efcc..3bb0f9a7777081a6c97f9b78b69ebaed3abf37eb 100644
--- a/bob/learn/tensorflow/network/InceptionResnetV2.py
+++ b/bob/learn/tensorflow/network/InceptionResnetV2.py
@@ -252,7 +252,7 @@ def inception_resnet_v2_batch_norm(inputs,
         # Moving averages ends up in the trainable variables collection
         'variables_collections': [tf.GraphKeys.TRAINABLE_VARIABLES],
     }
-    
+    weight_decay = 5e-5
     with slim.arg_scope(
         [slim.conv2d, slim.fully_connected],
             weights_initializer=tf.truncated_normal_initializer(stddev=0.1),