diff --git a/tests/validation/CL/BatchNormalizationLayer.cpp b/tests/validation/CL/BatchNormalizationLayer.cpp
index 30dd70a..ef53515 100644
--- a/tests/validation/CL/BatchNormalizationLayer.cpp
+++ b/tests/validation/CL/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -47,6 +47,12 @@
 constexpr AbsoluteTolerance<float> tolerance_f16(0.01f);    /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
 constexpr AbsoluteTolerance<float> tolerance_qs8(3.0f);     /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */
 constexpr AbsoluteTolerance<float> tolerance_qs16(6.0f);    /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS16 */
+const auto                         act_infos = framework::dataset::make("ActivationInfo",
+{
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
 } // namespace
 
 TEST_SUITE(CL)
@@ -80,13 +86,16 @@
 
 // *INDENT-OFF*
 // clang-format off
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
                framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),    // Window shrink
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Mismatching data types
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Mismatching data types
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Invalid mean/var/beta/gamma shape
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point position
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Fused activation with fixed point not supported
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Unsupported fused activation
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Fused activation's a < b
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                      }),
@@ -96,6 +105,9 @@
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                        TensorInfo(),
                                                      })),
@@ -106,16 +118,31 @@
                                                      TensorInfo(TensorShape(5U), 1, DataType::F32),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::F32),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::F32),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                    })),
-               framework::dataset::make("Expected", { true, false, false, false, false, false, true, true})),
-               input_info, output_info, mvbg_info, expected)
+                framework::dataset::make("ActivationLayerInfo",{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+                                                    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::TANH),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 6.f),
+                                                     ActivationLayerInfo(),
+                                                     ActivationLayerInfo(),
+                                                   })),
+               framework::dataset::make("Expected", { true, false, false, false, false, false, false, false, false, true, true})),
+               input_info, output_info, mvbg_info, act_info, expected)
 {
     const auto &mean_info = mvbg_info;
     const auto &var_info = mvbg_info;
     const auto &beta_info = mvbg_info;
     const auto &gamma_info = mvbg_info;
-    bool has_error = bool(CLBatchNormalizationLayer::validate(&input_info.clone()->set_is_resizable(false), (output_info.total_size() == 0) ? nullptr : &output_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false), &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f));
+    bool has_error = bool(CLBatchNormalizationLayer::validate(&input_info.clone()->set_is_resizable(false), (output_info.total_size() == 0) ? nullptr : &output_info.clone()->set_is_resizable(false), &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false), &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info));
     ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
 }
 // clang-format on
@@ -123,7 +150,8 @@
 
 TEST_SUITE(Float)
 TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                   act_infos),
                                                                                                                    framework::dataset::make("DataType", DataType::F32)))
 {
     // Validate output
@@ -132,7 +160,8 @@
 TEST_SUITE_END()
 
 TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                  framework::dataset::make("ActivationInfo", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f))),
                                                                                                                   framework::dataset::make("DataType", DataType::F16)))
 {
     // Validate output
@@ -146,7 +175,8 @@
 using CLBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture<CLTensor, CLAccessor, CLBatchNormalizationLayer, T>;
 
 TEST_SUITE(QS8)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                       framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                        framework::dataset::make("DataType", DataType::QS8)),
                        framework::dataset::make("FractionalBits", 1, 6)))
 {
@@ -156,7 +186,8 @@
 TEST_SUITE_END()
 
 TEST_SUITE(QS16)
-FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, CLBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                       framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                        framework::dataset::make("DataType", DataType::QS16)),
                        framework::dataset::make("FractionalBits", 1, 14)))
 {
diff --git a/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp b/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
index a82149b..d817fc0 100644
--- a/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
+++ b/tests/validation/GLES_COMPUTE/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -45,6 +45,12 @@
 {
 constexpr AbsoluteTolerance<float> tolerance_f(0.00001f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::F32 */
 constexpr AbsoluteTolerance<float> tolerance_f16(0.01f);  /**< Tolerance value for comparing reference's output against implementation's output for DataType::F16 */
+const auto                         act_infos = framework::dataset::make("ActivationInfo",
+{
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
 } // namespace
 
 TEST_SUITE(GC)
@@ -78,7 +84,8 @@
 
 TEST_SUITE(Float)
 TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                  act_infos),
                                                                                                                   framework::dataset::make("DataType", DataType::F16)))
 {
     // Validate output
@@ -87,7 +94,8 @@
 TEST_SUITE_END()
 
 TEST_SUITE(FP32)
-FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, GCBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                   act_infos),
                                                                                                                    framework::dataset::make("DataType", DataType::F32)))
 {
     // Validate output
diff --git a/tests/validation/NEON/BatchNormalizationLayer.cpp b/tests/validation/NEON/BatchNormalizationLayer.cpp
index dfa32bb..3501c35 100644
--- a/tests/validation/NEON/BatchNormalizationLayer.cpp
+++ b/tests/validation/NEON/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -49,6 +49,12 @@
 #endif                                                   /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */
 constexpr AbsoluteTolerance<float> tolerance_qs8(3.0f);  /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS8 */
 constexpr AbsoluteTolerance<float> tolerance_qs16(6.0f); /**< Tolerance value for comparing reference's output against implementation's output for DataType::QS16 */
+const auto                         act_infos = framework::dataset::make("ActivationInfo",
+{
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 8.f, 2.f),
+});
 } // namespace
 
 TEST_SUITE(NEON)
@@ -82,13 +88,15 @@
 
 // *INDENT-OFF*
 // clang-format off
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(
+DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(
                framework::dataset::make("InputInfo", { TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32),    // Window shrink
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Mismatching data types
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Mismatching data types
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Invalid mean/var/beta/gamma shape
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Mismatching fixed point position
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2), // Fused activation with fixed point not supported
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),    // Fused activation's a < b
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                      }),
@@ -98,6 +106,8 @@
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F16),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::F32),
+                                                       TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 3),
                                                        TensorInfo(TensorShape(32U, 13U, 2U), 1, DataType::QS8, 2),
                                                        TensorInfo(),
                                                      })),
@@ -108,10 +118,23 @@
                                                      TensorInfo(TensorShape(5U), 1, DataType::F32),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::F32),
+                                                     TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                      TensorInfo(TensorShape(2U), 1, DataType::QS8, 2),
                                                    })),
-               framework::dataset::make("Expected", { true, false, false, false, false, false, true, true})),
-               input_info, output_info, mvbg_info, expected)
+               framework::dataset::make("ActivationLayerInfo",{ ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+                                                    ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 6.f, 2.f),
+                                                     ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::LU_BOUNDED_RELU, 2.f, 6.f),
+                                                     ActivationLayerInfo(),
+                                                     ActivationLayerInfo(),
+                                                   })),
+               framework::dataset::make("Expected", { true, false, false, false, false, false, false, false, true, true})),
+               input_info, output_info, mvbg_info, act_info, expected)
 {
     const auto &mean_info = mvbg_info;
     const auto &var_info = mvbg_info;
@@ -120,14 +143,15 @@
     bool has_error = bool(NEBatchNormalizationLayer::validate(
             &input_info.clone()->set_is_resizable(false), output_info.total_size() ? &output_info.clone()->set_is_resizable(false) : nullptr,
             &mean_info.clone()->set_is_resizable(false), &var_info.clone()->set_is_resizable(false),
-            &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f));
+            &beta_info.clone()->set_is_resizable(false), &gamma_info.clone()->set_is_resizable(false), 1.f, act_info));
     ARM_COMPUTE_EXPECT(has_error == expected, framework::LogLevel::ERRORS);
 }
 // clang-format on
 // *INDENT-ON*
 
 TEST_SUITE(Float)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<float>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                   act_infos),
                                                                                                                    framework::dataset::make("DataType", DataType::F32)))
 {
     // Validate output
@@ -137,7 +161,8 @@
 
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 TEST_SUITE(Float16)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixture<half>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                                                                                                                  act_infos),
                                                                                                                   framework::dataset::make("DataType", DataType::F16)))
 {
     // Validate output
@@ -151,7 +176,8 @@
 using NEBatchNormalizationLayerFixedPointFixture = BatchNormalizationLayerValidationFixedPointFixture<Tensor, Accessor, NEBatchNormalizationLayer, T>;
 
 TEST_SUITE(QS8)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int8_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                       framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                        framework::dataset::make("DataType", DataType::QS8)),
                        framework::dataset::make("FractionalBits", 1, 6)))
 {
@@ -161,7 +187,8 @@
 TEST_SUITE_END()
 
 TEST_SUITE(QS16)
-FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+FIXTURE_DATA_TEST_CASE(Random, NEBatchNormalizationLayerFixedPointFixture<int16_t>, framework::DatasetMode::PRECOMMIT, combine(combine(combine(datasets::RandomBatchNormalizationLayerDataset(),
+                       framework::dataset::make("ActivationInfo", ActivationLayerInfo())),
                        framework::dataset::make("DataType", DataType::QS16)),
                        framework::dataset::make("FractionalBits", 1, 14)))
 {
diff --git a/tests/validation/fixtures/BatchNormalizationLayerFixture.h b/tests/validation/fixtures/BatchNormalizationLayerFixture.h
index 298c9ca..e02c619 100644
--- a/tests/validation/fixtures/BatchNormalizationLayerFixture.h
+++ b/tests/validation/fixtures/BatchNormalizationLayerFixture.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -45,12 +45,12 @@
 {
 public:
     template <typename...>
-    void setup(TensorShape shape0, TensorShape shape1, float epsilon, DataType dt, int fractional_bits)
+    void setup(TensorShape shape0, TensorShape shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fractional_bits)
     {
         _fractional_bits = fractional_bits;
         _data_type       = dt;
-        _target          = compute_target(shape0, shape1, epsilon, dt, fractional_bits);
-        _reference       = compute_reference(shape0, shape1, epsilon, dt, fractional_bits);
+        _target          = compute_target(shape0, shape1, epsilon, act_info, dt, fractional_bits);
+        _reference       = compute_reference(shape0, shape1, epsilon, act_info, dt, fractional_bits);
     }
 
 protected:
@@ -85,7 +85,7 @@
         }
     }
 
-    TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, float epsilon, DataType dt, int fixed_point_position)
+    TensorType compute_target(const TensorShape &shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fixed_point_position)
     {
         // Create tensors
         TensorType src   = create_tensor<TensorType>(shape0, dt, 1, fixed_point_position);
@@ -97,7 +97,7 @@
 
         // Create and configure function
         FunctionType norm;
-        norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon);
+        norm.configure(&src, &dst, &mean, &var, &beta, &gamma, epsilon, act_info);
 
         ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
         ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
@@ -130,7 +130,7 @@
         return dst;
     }
 
-    SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, DataType dt, int fixed_point_position)
+    SimpleTensor<T> compute_reference(const TensorShape &shape0, const TensorShape &shape1, float epsilon, ActivationLayerInfo act_info, DataType dt, int fixed_point_position)
     {
         // Create reference
         SimpleTensor<T> ref_src{ shape0, dt, 1, fixed_point_position };
@@ -142,7 +142,7 @@
         // Fill reference
         fill(ref_src, ref_mean, ref_var, ref_beta, ref_gamma);
 
-        return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, fixed_point_position);
+        return reference::batch_normalization_layer(ref_src, ref_mean, ref_var, ref_beta, ref_gamma, epsilon, act_info, fixed_point_position);
     }
 
     TensorType      _target{};
@@ -156,9 +156,9 @@
 {
 public:
     template <typename...>
-    void setup(TensorShape shape0, TensorShape shape1, float epsilon, DataType dt)
+    void setup(TensorShape shape0, TensorShape shape1, float epsilon, ActivationLayerInfo act_info, DataType dt)
     {
-        BatchNormalizationLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, epsilon, dt, 0);
+        BatchNormalizationLayerValidationFixedPointFixture<TensorType, AccessorType, FunctionType, T>::setup(shape0, shape1, epsilon, act_info, dt, 0);
     }
 };
 } // namespace validation
diff --git a/tests/validation/reference/BatchNormalizationLayer.cpp b/tests/validation/reference/BatchNormalizationLayer.cpp
index e4446d1..a9d9f03 100644
--- a/tests/validation/reference/BatchNormalizationLayer.cpp
+++ b/tests/validation/reference/BatchNormalizationLayer.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -23,6 +23,8 @@
  */
 #include "BatchNormalizationLayer.h"
 
+#include "ActivationLayer.h"
+
 #include "tests/validation/FixedPoint.h"
 #include "tests/validation/Helpers.h"
 
@@ -37,8 +39,9 @@
 // Batch Normalization Layer for fixed point type
 template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type *>
 SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
-                                          int fixed_point_position)
+                                          ActivationLayerInfo act_info, int fixed_point_position)
 {
+    ARM_COMPUTE_UNUSED(act_info);
     SimpleTensor<T> result(src.shape(), src.data_type());
 
     const auto cols       = static_cast<int>(src.shape()[0]);
@@ -79,7 +82,7 @@
 // Batch Normalization Layer for floating point type
 template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type *>
 SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
-                                          int fixed_point_position)
+                                          ActivationLayerInfo act_info, int fixed_point_position)
 {
     ARM_COMPUTE_UNUSED(fixed_point_position);
 
@@ -103,21 +106,28 @@
                     const float numerator   = src[pos] - mean[i];
                     const float x_bar       = numerator / denominator;
                     result[pos]             = beta[i] + x_bar * gamma[i];
+                    ;
                 }
             }
         }
     }
+
+    if(act_info.enabled())
+    {
+        result = activation_layer(result, act_info);
+    }
+
     return result;
 }
 template SimpleTensor<float> batch_normalization_layer(const SimpleTensor<float> &src, const SimpleTensor<float> &mean, const SimpleTensor<float> &var, const SimpleTensor<float> &beta,
-                                                       const SimpleTensor<float> &gamma, float epsilon, int fixed_point_position);
+                                                       const SimpleTensor<float> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
 template SimpleTensor<int8_t> batch_normalization_layer(const SimpleTensor<int8_t> &src, const SimpleTensor<int8_t> &mean, const SimpleTensor<int8_t> &var, const SimpleTensor<int8_t> &beta,
-                                                        const SimpleTensor<int8_t> &gamma, float epsilon, int fixed_point_position);
+                                                        const SimpleTensor<int8_t> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
 template SimpleTensor<int16_t> batch_normalization_layer(const SimpleTensor<int16_t> &src, const SimpleTensor<int16_t> &mean, const SimpleTensor<int16_t> &var, const SimpleTensor<int16_t> &beta,
-                                                         const SimpleTensor<int16_t> &gamma, float epsilon, int fixed_point_position);
+                                                         const SimpleTensor<int16_t> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
 template SimpleTensor<half> batch_normalization_layer(const SimpleTensor<half> &src, const SimpleTensor<half> &mean, const SimpleTensor<half> &var,
                                                       const SimpleTensor<half> &beta,
-                                                      const SimpleTensor<half> &gamma, float epsilon, int fixed_point_position);
+                                                      const SimpleTensor<half> &gamma, float epsilon, ActivationLayerInfo act_info, int fixed_point_position);
 
 } // namespace reference
 } // namespace validation
diff --git a/tests/validation/reference/BatchNormalizationLayer.h b/tests/validation/reference/BatchNormalizationLayer.h
index 1a554ad..329909d 100644
--- a/tests/validation/reference/BatchNormalizationLayer.h
+++ b/tests/validation/reference/BatchNormalizationLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -37,11 +37,13 @@
 {
 template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr>
 SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
-                                          int fixed_point_position);
+                                          ActivationLayerInfo act_info,
+                                          int                 fixed_point_position);
 
 template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type * = nullptr>
 SimpleTensor<T> batch_normalization_layer(const SimpleTensor<T> &src, const SimpleTensor<T> &mean, const SimpleTensor<T> &var, const SimpleTensor<T> &beta, const SimpleTensor<T> &gamma, float epsilon,
-                                          int fixed_point_position);
+                                          ActivationLayerInfo act_info,
+                                          int                 fixed_point_position);
 } // namespace reference
 } // namespace validation
 } // namespace test