diff --git a/src/otx/algorithms/segmentation/adapters/openvino/task.py b/src/otx/algorithms/segmentation/adapters/openvino/task.py
index 268eb2e933a..270216505c6 100644
--- a/src/otx/algorithms/segmentation/adapters/openvino/task.py
+++ b/src/otx/algorithms/segmentation/adapters/openvino/task.py
@@ -240,6 +240,8 @@ def add_prediction(
                     current_label_soft_prediction = soft_prediction[:, :, label_index]
                     if process_soft_prediction:
                         current_label_soft_prediction = get_activation_map(current_label_soft_prediction)
+                    else:
+                        current_label_soft_prediction = (current_label_soft_prediction * 255).astype(np.uint8)
                     result_media = ResultMediaEntity(
                         name=label.name,
                         type="soft_prediction",
diff --git a/src/otx/algorithms/segmentation/task.py b/src/otx/algorithms/segmentation/task.py
index a3a8923454b..08860a3e168 100644
--- a/src/otx/algorithms/segmentation/task.py
+++ b/src/otx/algorithms/segmentation/task.py
@@ -290,6 +290,8 @@ def _add_predictions_to_dataset(self, prediction_results, dataset, dump_soft_pre
                     current_label_soft_prediction = soft_prediction[:, :, label_index]
                     if process_soft_prediction:
                         current_label_soft_prediction = get_activation_map(current_label_soft_prediction)
+                    else:
+                        current_label_soft_prediction = (current_label_soft_prediction * 255).astype(np.uint8)
                     result_media = ResultMediaEntity(
                         name=label.name,
                         type="soft_prediction",
diff --git a/tests/unit/algorithms/classification/test_xai_classification_validity.py b/tests/unit/algorithms/classification/test_xai_classification_validity.py
index 8f15ede6133..1ec20d0c2c1 100644
--- a/tests/unit/algorithms/classification/test_xai_classification_validity.py
+++ b/tests/unit/algorithms/classification/test_xai_classification_validity.py
@@ -54,4 +54,4 @@ def test_saliency_map_cls(self, template):
         assert len(saliency_maps) == 2
         assert saliency_maps[0].ndim == 3
         assert saliency_maps[0].shape == (1000, 7, 7)
-        assert (saliency_maps[0][0][0] == self.ref_saliency_vals_cls[template.name]).all()
+        assert np.all(np.abs(saliency_maps[0][0][0] - self.ref_saliency_vals_cls[template.name]) <= 1)
diff --git a/tests/unit/algorithms/detection/test_xai_detection_validity.py b/tests/unit/algorithms/detection/test_xai_detection_validity.py
index 6ed47397992..3e903a0b5d6 100644
--- a/tests/unit/algorithms/detection/test_xai_detection_validity.py
+++ b/tests/unit/algorithms/detection/test_xai_detection_validity.py
@@ -80,7 +80,7 @@ def test_saliency_map_det(self, template):
         assert len(saliency_maps) == 2
         assert saliency_maps[0].ndim == 3
         assert saliency_maps[0].shape == self.ref_saliency_shapes[template.name]
-        assert (saliency_maps[0][0][0] == self.ref_saliency_vals_det[template.name]).all()
+        assert np.all(np.abs(saliency_maps[0][0][0] - self.ref_saliency_vals_det[template.name]) <= 1)
 
     @e2e_pytest_unit
     @pytest.mark.parametrize("template", templates_det, ids=templates_det_ids)