diff --git a/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp b/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp
index fa26b90..aa7af54 100644
--- a/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp
+++ b/src/core/NEON/kernels/NEArithmeticAdditionKernel.cpp
@@ -56,7 +56,7 @@
     constexpr int window_step_x         = 16 / sizeof(T);
     const auto    window_start_x        = static_cast<int>(window.x().start());
     const auto    window_end_x          = static_cast<int>(window.x().end());
-    const bool    is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool    is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     if(is_broadcast_across_x)
     {
@@ -152,7 +152,7 @@
     const int  window_step_x         = 16;
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     const UniformQuantizationInfo iq1_info = in1->info()->quantization_info().uniform();
     const UniformQuantizationInfo iq2_info = in2->info()->quantization_info().uniform();
@@ -345,7 +345,7 @@
     const int  window_step_x         = 16;
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     const UniformQuantizationInfo iq1_info = in1->info()->quantization_info().uniform();
     const UniformQuantizationInfo iq2_info = in2->info()->quantization_info().uniform();
@@ -537,7 +537,7 @@
     const int  window_step_x         = 8;
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     const UniformQuantizationInfo iq1_info = in1->info()->quantization_info().uniform();
     const UniformQuantizationInfo iq2_info = in2->info()->quantization_info().uniform();
diff --git a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp b/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp
index bdd356a..187e97d 100644
--- a/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp
+++ b/src/core/NEON/kernels/NEArithmeticSubtractionKernel.cpp
@@ -67,7 +67,7 @@
     constexpr int window_step_x         = 16 / sizeof(T);
     const auto    window_start_x        = static_cast<int>(window.x().start());
     const auto    window_end_x          = static_cast<int>(window.x().end());
-    const bool    is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool    is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     Iterator input1(in1, window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()));
     Iterator input2(in2, window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()));
@@ -178,7 +178,7 @@
     const int  window_step_x         = 16;
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     const UniformQuantizationInfo iq1_info = in1->info()->quantization_info().uniform();
     const UniformQuantizationInfo iq2_info = in2->info()->quantization_info().uniform();
@@ -372,7 +372,7 @@
     const int  window_step_x         = 8;
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     const UniformQuantizationInfo iq1_info = in1->info()->quantization_info().uniform();
     const UniformQuantizationInfo iq2_info = in2->info()->quantization_info().uniform();
diff --git a/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp b/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp
index bb4e9a6..412ae24 100644
--- a/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp
+++ b/src/core/NEON/kernels/NEElementwiseOperationKernel.cpp
@@ -656,7 +656,7 @@
     const int  window_step_x         = std::min(16 / static_cast<int>(sizeof(OutputScalarType)), 8);
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     if(is_broadcast_across_x)
     {
@@ -735,7 +735,7 @@
     const int  window_step_x         = 16;
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     const UniformQuantizationInfo output_qinfo = out->info()->quantization_info().uniform();
 
@@ -843,7 +843,7 @@
     const int  window_step_x         = 16;
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     const UniformQuantizationInfo output_qinfo = out->info()->quantization_info().uniform();
 
@@ -950,7 +950,7 @@
     const int  window_step_x         = 16;
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     const UniformQuantizationInfo output_qinfo = out->info()->quantization_info().uniform();
 
diff --git a/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp b/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp
index f646ea5..39517f6 100644
--- a/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp
+++ b/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp
@@ -156,7 +156,7 @@
     const int  window_step_x         = 16 / sizeof(T);
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     const UniformQuantizationInfo output_qua_info = out->info()->quantization_info().uniform();
     const UniformQuantizationInfo tmp_qua_info    = { output_qua_info.scale / scale, output_qua_info.offset };
@@ -785,7 +785,7 @@
     const int  window_step_x         = 8;
     const auto window_start_x        = static_cast<int>(window.x().start());
     const auto window_end_x          = static_cast<int>(window.x().end());
-    const bool is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     if(is_broadcast_across_x)
     {
@@ -935,7 +935,7 @@
     constexpr int window_step_x         = 16 / sizeof(float);
     const auto    window_start_x        = static_cast<int>(window.x().start());
     const auto    window_end_x          = static_cast<int>(window.x().end());
-    const bool    is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool    is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     using ExactTagType = typename wrapper::traits::neon_vector<float, window_step_x>::tag_type;
 
@@ -1033,7 +1033,7 @@
     constexpr int window_step_x         = 8 / sizeof(float);
     const auto    window_start_x        = static_cast<int>(window.x().start());
     const auto    window_end_x          = static_cast<int>(window.x().end());
-    const bool    is_broadcast_across_x = (input1_win.x().step() == 0) || (input2_win.x().step() == 0);
+    const bool    is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x();
 
     using ExactTagType = typename wrapper::traits::neon_vector<float, 2>::tag_type;