diff --git a/src/armnnTfLiteParser/TfLiteParser.cpp b/src/armnnTfLiteParser/TfLiteParser.cpp
index c787212..ee4cadd 100644
--- a/src/armnnTfLiteParser/TfLiteParser.cpp
+++ b/src/armnnTfLiteParser/TfLiteParser.cpp
@@ -524,7 +524,7 @@
         }
     }
 
-    float quantizationScale = 0.0f;
+    float quantizationScale = 1.0f;
     int32_t quantizationOffset = 0;
 
     if (tensorPtr->quantization.get())
diff --git a/src/armnnTfLiteParser/test/DetectionPostProcess.cpp b/src/armnnTfLiteParser/test/DetectionPostProcess.cpp
index 2f9f29c..9d807d8 100644
--- a/src/armnnTfLiteParser/test/DetectionPostProcess.cpp
+++ b/src/armnnTfLiteParser/test/DetectionPostProcess.cpp
@@ -1,5 +1,5 @@
 //
-// Copyright © 2017 Arm Ltd and Contributors. All rights reserved.
+// Copyright © 2017, 2023 Arm Ltd and Contributors. All rights reserved.
 // SPDX-License-Identifier: MIT
 //
 
@@ -288,10 +288,10 @@
     armnn::TensorInfo scoresTensor(armnn::TensorShape({ 1, 6, 3 }), armnn::DataType::QAsymmU8,
                                                       0.00999999978f, 0);
 
-    armnn::TensorInfo detectionBoxesTensor(armnn::TensorShape({ 1, 3, 4 }), armnn::DataType::Float32, 0, 0);
-    armnn::TensorInfo detectionClassesTensor(armnn::TensorShape({ 1, 3 }), armnn::DataType::Float32, 0, 0);
-    armnn::TensorInfo detectionScoresTensor(armnn::TensorShape({ 1, 3 }), armnn::DataType::Float32, 0, 0);
-    armnn::TensorInfo numDetectionsTensor(armnn::TensorShape({ 1} ), armnn::DataType::Float32, 0, 0);
+    armnn::TensorInfo detectionBoxesTensor(armnn::TensorShape({ 1, 3, 4 }), armnn::DataType::Float32);
+    armnn::TensorInfo detectionClassesTensor(armnn::TensorShape({ 1, 3 }), armnn::DataType::Float32);
+    armnn::TensorInfo detectionScoresTensor(armnn::TensorShape({ 1, 3 }), armnn::DataType::Float32);
+    armnn::TensorInfo numDetectionsTensor(armnn::TensorShape({ 1 } ), armnn::DataType::Float32);
 
     CHECK(IsConnected(boxEncodingLayer, detectionPostProcessLayer, 0, 0, boxEncodingTensor));
     CHECK(IsConnected(scoresLayer, detectionPostProcessLayer, 0, 1, scoresTensor));