diff --git a/src/core/NEON/kernels/NEFuseBatchNormalizationKernel.h b/src/core/NEON/kernels/NEFuseBatchNormalizationKernel.h
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+/*
+ * Copyright (c) 2018-2020 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#ifndef ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H
+#define ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H
+
+#include "src/core/NEON/INEKernel.h"
+
+namespace arm_compute
+{
+// Forward declarations
+class ITensor;
+
+/** OpenNE kernel to fuse the batch normalization node to a preceding convolution node */
+class NEFuseBatchNormalizationKernel : public INEKernel
+{
+public:
+    const char *name() const override
+    {
+        return "NEFuseBatchNormalizationKernel";
+    }
+    /** Default constructor */
+    NEFuseBatchNormalizationKernel();
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    NEFuseBatchNormalizationKernel(const NEFuseBatchNormalizationKernel &) = delete;
+    /** Prevent instances of this class from being copied (As this class contains pointers) */
+    NEFuseBatchNormalizationKernel &operator=(const NEFuseBatchNormalizationKernel &) = delete;
+    /** Allow instances of this class to be moved */
+    NEFuseBatchNormalizationKernel(NEFuseBatchNormalizationKernel &&) = default;
+    /** Allow instances of this class to be moved */
+    NEFuseBatchNormalizationKernel &operator=(NEFuseBatchNormalizationKernel &&) = default;
+    /** Default destructor */
+    ~NEFuseBatchNormalizationKernel() = default;
+    /** Set the source, destination of the kernel
+     *
+     * @param[in]  input_weights Input weights tensor for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC
+     * @param[in]  bn_mean       Batch normalization layer mean tensor. Same as @p input_weights
+     * @param[in]  bn_var        Batch normalization layer variance tensor. Same as @p input_weights
+     * @param[out] fused_weights (Optional) Output fused weights tensor. It can be a nullptr in case of in-place computation. Same as @p input_weights
+     * @param[out] fused_bias    (Optional) Output fused bias tensor. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights
+     * @param[in]  input_bias    (Optional) Input bias tensor for convolution or depthwise convolution layer. It can be a nullptr in case the bias tensor is not required. Same as @p input_weights
+     * @param[in]  bn_beta       (Optional) Batch normalization layer beta tensor. It can be a nullptr in case the beta tensor is not required. Same as @p input_weights
+     *                           @note if nullptr, bn_beta is set to 0.0
+     * @param[in]  bn_gamma      (Optional) Batch normalization layer gamma tensor. It can be a nullptr in case the gamma tensor is not required. Same as @p input_weights
+     *                           @note if nullptr, bn_gamma is set to 1.0
+     * @param[in]  epsilon       (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f.
+     * @param[in]  fbn_type      (Optional) Fused batch normalization type. Defaults to CONVOLUTION.
+     */
+    void configure(const ITensor *input_weights, const ITensor *bn_mean, const ITensor *bn_var, ITensor *fused_weights, ITensor *fused_bias,
+                   const ITensor *input_bias = nullptr, const ITensor *bn_beta = nullptr, const ITensor *bn_gamma = nullptr,
+                   float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION);
+    /** Static function to check if given info will lead to a valid configuration of @ref NEFuseBatchNormalizationKernel
+     *
+     * @param[in] input_weights Input weights tensor info for convolution or depthwise convolution layer. Data type supported: F16/F32. Data layout supported: NCHW, NHWC
+     * @param[in] bn_mean       Batch normalization layer mean tensor info. Same as @p input_weights
+     * @param[in] bn_var        Batch normalization layer variance tensor info. Same as @p input_weights
+     * @param[in] fused_weights (Optional) Output fused weights tensor info. It can be a nullptr in case of in-place computation. Same as @p input_weights
+     * @param[in] fused_bias    (Optional) Output fused bias tensor info. It can be a nullptr in case of in-place computation and input_bias != nullptr. Same as @p input_weights
+     * @param[in] input_bias    (Optional) Input bias tensor info for convolution or depthwise convolution layer. It can be a nullptr in case the bias tensor is not required. Same as @p input_weights
+     * @param[in] bn_beta       (Optional) Batch normalization layer beta tensor info. It can be a nullptr in case the beta tensor is not required. Same as @p input_weights
+     *                          @note if nullptr, bn_beta is set to 0.0
+     * @param[in] bn_gamma      (Optional) Batch normalization layer gamma tensor info. It can be a nullptr in case the gamma tensor is not required. Same as @p input_weights
+     *                          @note if nullptr, bn_gamma is set to 1.0
+     * @param[in] epsilon       (Optional) Batch normalization layer epsilon parameter. Defaults to 0.001f.
+     * @param[in] fbn_type      (Optional) Fused batch normalization type. Defaults to CONVOLUTION.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input_weights, const ITensorInfo *bn_mean, const ITensorInfo *bn_var,
+                           const ITensorInfo *fused_weights, const ITensorInfo *fused_bias,
+                           const ITensorInfo *input_bias = nullptr, const ITensorInfo *bn_beta = nullptr, const ITensorInfo *bn_gamma = nullptr,
+                           float epsilon = 0.001f, FuseBatchNormalizationType fbn_type = FuseBatchNormalizationType::CONVOLUTION);
+
+    // Inherited methods overridden:
+    void run(const Window &window, const ThreadInfo &info) override;
+
+private:
+    const ITensor *_input_weights;
+    const ITensor *_input_bias;
+    const ITensor *_bn_mean;
+    const ITensor *_bn_var;
+    const ITensor *_bn_gamma;
+    const ITensor *_bn_beta;
+    ITensor       *_fused_weights;
+    ITensor       *_fused_bias;
+    float          _epsilon;
+    bool           _run_in_place_weights;
+    bool           _run_in_place_bias;
+
+    using FuseBatchNormFunction = void(const ITensor *input_weights, const ITensor *input_bias, ITensor *fused_weights, ITensor *fused_bias,
+                                       const ITensor *bn_mean, const ITensor *bn_var, const ITensor *bn_beta, const ITensor *bn_gamma, float epsilon, const Window &window);
+
+    FuseBatchNormFunction *_func;
+};
+} // namespace arm_compute
+#endif /*ARM_COMPUTE_NEFUSEBATCHNORMALIZATIONKERNEL_H */