diff --git a/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
index 594d602..683aa79 100644
--- a/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
+++ b/arm_compute/runtime/CL/functions/CLWinogradConvolutionLayer.h
@@ -59,8 +59,9 @@
     CLWinogradConvolutionLayer &operator=(CLWinogradConvolutionLayer &&) = default;
     /** Set the input and output tensors.
      *
-     * @note: This function only works with 3x3 and 5x5 kernels along with unit strides
-     * @note  Some Winograd configurations (i.e. F(4x4, 3x3) and F(4x4, 5x5)) are supported only with enable_fast_math = true
+     * @note: This function only works with 3x3,3x1,1x3,5x5,5x1 and 1x5 kernels along with unit strides for NCHW data layout
+     * @note: This function only works with 3x3, 3x1, 1x3 and 5x5 kernels along with unit strides for NHWC data layout
+     * @note  Some Winograd configurations (i.e. F(4x4, 5x5)) are supported only with enable_fast_math = true
      *
      * @param[in]  input            Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
      *                              while every optional dimension from 4 and above represent a batch of inputs.
@@ -78,8 +79,9 @@
                    const ActivationLayerInfo &act_info = ActivationLayerInfo(), bool enable_fast_math = false);
     /** Static function to check if given info will lead to a valid configuration of @ref CLWinogradConvolutionLayer
      *
-     * @note: This function only works with 3x3 and 5x5 kernels along with unit strides
-     * @note  Some Winograd configurations (i.e. F(4x4, 3x3) and F(4x4, 5x5)) are supported only with enable_fast_math = true
+     * @note: This function only works with 3x3,3x1,1x3,5x5,5x1 and 1x5 kernels along with unit strides for NCHW data layout
+     * @note: This function only works with 3x3 and 5x5 kernels along with unit strides for NHWC data layout
+     * @note  Some Winograd configurations (i.e. F(4x4, 5x5)) are supported only with enable_fast_math = true
      *
      * @param[in]  input            Source tensor. 3 lower dimensions represent a single input [width, height, IFM],
      *                              while every optional dimension from 4 and above represent a batch of inputs.
diff --git a/arm_compute/runtime/CL/functions/CLWinogradInputTransform.h b/arm_compute/runtime/CL/functions/CLWinogradInputTransform.h
index 64d3e80..1f89455 100644
--- a/arm_compute/runtime/CL/functions/CLWinogradInputTransform.h
+++ b/arm_compute/runtime/CL/functions/CLWinogradInputTransform.h
@@ -39,8 +39,14 @@
 public:
     /** Set the input and output tensors.
      *
-     * @note Winograd input transform supports the following configurations:
-     *       F(output tile, kernel size):F(2x2, 3x3), F(4x4, 3x3), F(4x4, 5x5)
+     * @note Winograd input transform supports the following configurations for NCWH data layout
+     *       F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3),
+     *                                   F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
+     *                                   F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     * @note Winograd input transform supports the following configurations for NHWC data layout
+     *       F(output tile, kernel size):F(4x4, 3x3),
+     *                                   F(4x4, 5x5)
      *       Strides: only unit strides
      *
      * @param[in] input         The input tensor to transform. Data types supported: F32
@@ -50,8 +56,14 @@
     void configure(ICLTensor *input, ICLTensor *output, const WinogradInfo &winograd_info);
     /**  Static function to check if given info will lead to a valid configuration of @ref CLWinogradInputTransform.
      *
-     * @note Winograd input transform supports the following configurations:
-     *       F(output tile, kernel size):F(2x2, 3x3), F(4x4, 3x3), F(4x4, 5x5)
+     * @note Winograd input transform supports the following configurations for NCWH data layout
+     *       F(output tile, kernel size):F(2x2, 3x3), F(2x1, 3x1), F(1x2, 1x3),
+     *                                   F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3),
+     *                                   F(4x4, 5x5), F(4x1, 5x1), F(1x4, 1x5)
+     *
+     * @note Winograd input transform supports the following configurations for NHWC data layout
+     *       F(output tile, kernel size):F(4x4, 3x3), F(4x1, 3x1), F(1x4, 1x3)
+     *                                   F(4x4, 5x5)
      *       Strides: only unit strides
      *
      * @param[in] input         The input tensor to transform. Data types supported: F32