diff --git a/Examples/Learning/SVMGenericKernelImageClassificationExample.cxx b/Examples/Learning/SVMGenericKernelImageClassificationExample.cxx
index f9111b7d3f2513cc00932549899fe8e2ed470ef5..5e14faac78e29d017a9b0cf8852b4cedc111e391 100644
--- a/Examples/Learning/SVMGenericKernelImageClassificationExample.cxx
+++ b/Examples/Learning/SVMGenericKernelImageClassificationExample.cxx
@@ -33,8 +33,7 @@
 // classification on images with a user-defined kernel.
 // In this example, we will use an SVM model estimated in the previous
 // section to separate between water and non-water pixels by using the RGB
-// values only. The images used for this example are shown in
-// figure~\ref{fig:SVMROIS}.
+// values only.
 // The first thing to do is include the header file for the
 // class as well as the header of the appropriated kernel to be used.
 //
@@ -98,7 +97,7 @@ int main(int argc, char* argv[])
 // Software Guide : BeginLatex
 //
 // After instantiation, we can load a model saved to a file (see
-// section \ref{sec:LearningWithImages} for an example of model
+// section \ref{ssec:LearningFromImages} for an example of model
 // estimation and storage to a file).
 //
 // When using a user defined kernel, an explicit instanciation has
diff --git a/Examples/Learning/SVMGenericKernelImageModelEstimatorExample.cxx b/Examples/Learning/SVMGenericKernelImageModelEstimatorExample.cxx
index f69af05ea81e25436520453d79e507171b732bab..1e411f9cb66bc1ccc22577cf69d1b94c5a66441e 100644
--- a/Examples/Learning/SVMGenericKernelImageModelEstimatorExample.cxx
+++ b/Examples/Learning/SVMGenericKernelImageModelEstimatorExample.cxx
@@ -23,7 +23,7 @@
 // This example illustrates the modifications to be added to the
 // use of \doxygen{otb}{SVMImageModelEstimator} in order to add a
 // user defined kernel. This initial program has been explained in section
-// \ref{sec:LearningWithImages}.
+// \ref{ssec:LearningFromImages}.
 //
 // The first thing to do is to include the header file for the new kernel.
 //
diff --git a/Examples/Markov/MarkovRegularizationExample.cxx b/Examples/Markov/MarkovRegularizationExample.cxx
index 3ee4ab5a757a89d3af93ed6ae73cda2dd759f371..3107b8faf78f15ca1ac023579308896e2b6bc5ba 100644
--- a/Examples/Markov/MarkovRegularizationExample.cxx
+++ b/Examples/Markov/MarkovRegularizationExample.cxx
@@ -28,7 +28,7 @@
 // This example illustrates the use of the \doxygen{otb}{MarkovRandomFieldFilter}.
 // to regularize a classification obtained previously by another classifier. Here
 // we will apply the regularization to the output of an SVM classifier presented
-// in \ref{sec:ImageClassification}.
+// in \ref{ssec:LearningFromImages}.
 //
 // The reference image and the starting image are both going to be the original
 // classification. Both regularization and fidelity energy are defined by Potts model.