diff --git a/docs/user_guide/how_to_build_and_run_examples.dox b/docs/user_guide/how_to_build_and_run_examples.dox
index 775cb6a..0b8a23b 100644
--- a/docs/user_guide/how_to_build_and_run_examples.dox
+++ b/docs/user_guide/how_to_build_and_run_examples.dox
@@ -1,5 +1,5 @@
 ///
-/// Copyright (c) 2017-2023 Arm Limited.
+/// Copyright (c) 2017-2024 Arm Limited.
 ///
 /// SPDX-License-Identifier: MIT
 ///
@@ -542,19 +542,28 @@
 	cmake .. -DCMAKE_BUILD_TYPE=Release -DARM_COMPUTE_OPENMP=1 -DARM_COMPUTE_WERROR=0 -DARM_COMPUTE_BUILD_EXAMPLES=1 -DARM_COMPUTE_BUILD_TESTING=1 -DCMAKE_INSTALL_LIBDIR=.
 	cmake --build . -j32
 
-@section S1_8_fixed_format Building with support for fixed format kernels
+@section S1_9_fixed_format Building with support for fixed format kernels
 
-@subsection S1_8_1_intro_to_fixed_format_kernels What are fixed format kernels?
+@subsection S1_9_1_intro_to_fixed_format_kernels What are fixed format kernels?
 
 The GEMM kernels used for convolutions and fully-connected layers in Compute Library employ memory layouts optimized for each kernel implementation. This then requires the supplied weights to be re-ordered into a buffer ready for consumption by the GEMM kernel. Where Compute Library is being called from a framework or library which implements operator caching, the re-ordering of the inputted weights into an intermediate buffer may no longer be desirable. When using a cached operator, the caller may wish to re-write the weights tensor, and re-run the operator using the updated weights. With the default GEMM kernels in Compute Library, the GEMM will be executed with the old weights, leading to incorrect results.
 
 To address this, Compute Library provides a set of GEMM kernels which use a common blocked memory format. These kernels consume the input weights directly from the weights buffer and do not execute an intermediate pre-transpose step. With this approach, it is the responsibility of the user (in this case the calling framework) to ensure that the weights are re-ordered into the required memory format. @ref NEGEMM::has_opt_impl is a static function that queries whether there exists fixed-format kernel, and if so will return in the expected weights format. The supported weight formats are enumerated in @ref arm_compute::WeightFormat.
 
-@subsection S1_8_2_building_fixed_format Building with fixed format kernels
+@subsection S1_9_2_building_fixed_format Building with fixed format kernels
 
 Fixed format kernels are only available for the CPU backend. To build Compute Library with fixed format kernels set fixed_format_kernels=1:
 
         scons Werror=1 debug=0 neon=1 opencl=0 embed_kernels=0 os=linux multi_isa=1 build=native cppthreads=1 openmp=0 fixed_format_kernels=1
 
+@section S1_10_doxygen Building the Doxygen Documentation
+
+This documentation has been generated using the following shell command:
+
+        $ ./scripts/generate_documentation.sh
+
+This requires Doxygen to be installed and available on your system.
+
 */
+
 } // namespace arm_compute