diff --git a/src/runtime/CL/functions/CLConvolutionLayer.cpp b/src/runtime/CL/functions/CLConvolutionLayer.cpp
index 3d4fb11..faec4bb 100644
--- a/src/runtime/CL/functions/CLConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLConvolutionLayer.cpp
@@ -123,7 +123,9 @@
     ARM_COMPUTE_UNUSED(weights_info);
     ARM_COMPUTE_UNUSED(gpu_target);
 
-    if(dilation != Size2D(1U, 1U))
+    const size_t idx_c = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL);
+
+    if(dilation != Size2D(1U, 1U) || (input->dimension(idx_c) < 16))
     {
         return ConvolutionMethod::GEMM;
     }
diff --git a/src/runtime/NEON/functions/NEConvolutionLayer.cpp b/src/runtime/NEON/functions/NEConvolutionLayer.cpp
index 0ad4bab..69fb948 100644
--- a/src/runtime/NEON/functions/NEConvolutionLayer.cpp
+++ b/src/runtime/NEON/functions/NEConvolutionLayer.cpp
@@ -104,16 +104,16 @@
                                                              const ITensorInfo *output, const PadStrideInfo &conv_info,
                                                              const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info)
 {
-    ARM_COMPUTE_ERROR_ON_NULLPTR(input);
-    ARM_COMPUTE_ERROR_ON_NULLPTR(output);
-    ARM_COMPUTE_ERROR_ON_NULLPTR(weights);
+    ARM_COMPUTE_ERROR_ON_NULLPTR(input, output, weights);
     ARM_COMPUTE_UNUSED(output);
     ARM_COMPUTE_UNUSED(weights_info);
 
     const size_t idx_w = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::WIDTH);
     const size_t idx_h = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::HEIGHT);
+    const size_t idx_c = get_data_layout_dimension_index(input->data_layout(), DataLayoutDimension::CHANNEL);
 
-    if((input->data_type() == DataType::F32) && (input->data_layout() == DataLayout::NCHW) && (weights->dimension(idx_w) == 3) && (weights->dimension(idx_h) == 3) && (weights->num_dimensions() <= 4)
+    if((input->data_type() == DataType::F32) && (input->data_layout() == DataLayout::NCHW) && (input->dimension(idx_c) > 16) && (weights->dimension(idx_w) == 3) && (weights->dimension(idx_h) == 3)
+       && (weights->num_dimensions() <= 4)
        && (conv_info.stride().first == 1) && (conv_info.stride().second == 1) && (dilation == Size2D(1U, 1U)) && (!act_info.enabled()))
     {
         //FIXME Until COMPMID-1041 is implemented Winograd is slower than GEMM on A53.