diff --git a/src/twomartens/masterthesis/cli.py b/src/twomartens/masterthesis/cli.py
index 72b3c3b..a6b5990 100644
--- a/src/twomartens/masterthesis/cli.py
+++ b/src/twomartens/masterthesis/cli.py
@@ -263,7 +263,8 @@ def _ssd_test(args: argparse.Namespace) -> None:
     _init_eager_mode()
     
     batch_size, image_size, learning_rate, \
-        forward_passes_per_image, nr_classes, iou_threshold, dropout_rate, top_k, nr_trajectories, \
+        forward_passes_per_image, nr_classes, iou_threshold, dropout_rate, \
+        entropy_threshold, top_k, nr_trajectories, \
         coco_path, output_path, weights_path, ground_truth_path = _ssd_test_get_config_values(args, conf.get_property)
     
     use_dropout = _ssd_is_dropout(args)
@@ -304,6 +305,7 @@ def _ssd_test(args: argparse.Namespace) -> None:
                 image_size,
                 batch_size,
                 forward_passes_per_image,
+                entropy_threshold,
                 output_path,
                 coco_path,
                 use_dropout,
@@ -500,7 +502,7 @@ def _ssd_train_get_config_values(config_get: Callable[[str], Union[str, float, i
 
 def _ssd_test_get_config_values(args: argparse.Namespace,
                                 config_get: Callable[[str], Union[str, float, int, bool]]
-                                ) -> Tuple[int, int, float, int, int, float, float, int, int,
+                                ) -> Tuple[int, int, float, int, int, float, float, float, int, int,
                                            str, str, str, str]:
     
     batch_size = config_get("Parameters.batch_size")
@@ -510,6 +512,7 @@ def _ssd_test_get_config_values(args: argparse.Namespace,
     nr_classes = config_get("Parameters.nr_classes")
     iou_threshold = config_get("Parameters.ssd_iou_threshold")
     dropout_rate = config_get("Parameters.ssd_dropout_rate")
+    entropy_threshold = config_get("Parameters.ssd_entropy_threshold")
     top_k = config_get("Parameters.ssd_top_k")
     nr_trajectories = config_get("Parameters.nr_trajectories")
 
@@ -529,6 +532,7 @@ def _ssd_test_get_config_values(args: argparse.Namespace,
         nr_classes,
         iou_threshold,
         dropout_rate,
+        entropy_threshold,
         top_k,
         nr_trajectories,
         #
diff --git a/src/twomartens/masterthesis/config.py b/src/twomartens/masterthesis/config.py
index c29ff61..0c13604 100644
--- a/src/twomartens/masterthesis/config.py
+++ b/src/twomartens/masterthesis/config.py
@@ -59,6 +59,7 @@ _CONFIG_PROPS = {
         "ssd_iou_threshold": (float, "0.45"),
         "ssd_top_k": (int, "200"),
         "ssd_dropout_rate": (float, "0.5"),
+        "ssd_entropy_threshold": (float, "2.5"),
         "nr_trajectories": (int, "-1")
     }
 }
diff --git a/src/twomartens/masterthesis/ssd.py b/src/twomartens/masterthesis/ssd.py
index 1d9bcde..a33fa30 100644
--- a/src/twomartens/masterthesis/ssd.py
+++ b/src/twomartens/masterthesis/ssd.py
@@ -145,6 +145,7 @@ def predict(generator: callable,
             image_size: int,
             batch_size: int,
             forward_passes_per_image: int,
+            entropy_threshold: float,
             output_path: str,
             coco_path: str,
             use_dropout: bool,
@@ -162,6 +163,7 @@ def predict(generator: callable,
         batch_size: number of items in every batch
         forward_passes_per_image: specifies number of forward passes per image
             used by DropoutSSD
+        entropy_threshold: specifies the threshold for the entropy
         output_path: the path in which the results should be saved
         coco_path: the path to the COCO data set
         use_dropout: if True, multiple forward passes and observations will be used
@@ -185,7 +187,8 @@ def predict(generator: callable,
                   decode_func=functools.partial(
                       _decode_predictions,
                       decode_func=ssd_output_decoder.decode_detections_fast,
-                      image_size=image_size
+                      image_size=image_size,
+                      entropy_threshold=entropy_threshold
                   ),
                   transform_func=functools.partial(
                       _transform_predictions,
@@ -319,12 +322,14 @@ def _predict_vanilla_step(inputs: np.ndarray, model: tf.keras.models.Model) -> n
 
 def _decode_predictions(predictions: np.ndarray,
                         decode_func: callable,
-                        image_size: int) -> np.ndarray:
+                        image_size: int,
+                        entropy_threshold: float) -> np.ndarray:
     return decode_func(
         y_pred=predictions,
         img_width=image_size,
         img_height=image_size,
-        input_coords="corners"
+        input_coords="corners",
+        entropy_threshold=entropy_threshold
     )