diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h
index 434291b..fe20699 100644
--- a/tests/validation/fixtures/ConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/ConvolutionLayerFixture.h
@@ -88,7 +88,12 @@
         {
             // Check if its a "fully connected" convolution
             const bool is_fully_connected_convolution = (output_shape.x() == 1 && output_shape.y() == 1);
-            const bool is_optimised                   = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV7 && data_type == DataType::F32;
+            bool       is_optimised                   = false;
+#if defined(__arm__)
+            is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU == CPUTarget::ARMV7 && data_type == DataType::F32;
+#elif defined(__aarch64__)
+            is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV8 && data_type == DataType::F32;
+#endif /* defined(__arm__) || defined(__aarch64__) */
 
             reshaped_weights_shape.collapse(3);
 
@@ -143,7 +148,12 @@
         if(!reshape_weights)
         {
             const bool is_fully_connected_convolution = (output_shape.x() == 1 && output_shape.y() == 1);
-            const bool is_optimised                   = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV7 && data_type == DataType::F32;
+            bool       is_optimised                   = false;
+#if defined(__arm__)
+            is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU == CPUTarget::ARMV7 && data_type == DataType::F32;
+#elif defined(__aarch64__)
+            is_optimised = std::is_same<FunctionType, NEConvolutionLayer>::value && NEScheduler::get().cpu_info().CPU >= CPUTarget::ARMV8 && data_type == DataType::F32;
+#endif /* defined(__arm__) || defined(__aarch64__) */
 
             TensorShape     tmp_weights_shape(weights_shape);
             SimpleTensor<T> tmp_weights(tmp_weights_shape, data_type, 1, fixed_point_position);