diff --git a/include/AutoencoderModel.txx b/include/AutoencoderModel.txx
index ee400c04a7a08bc980a237abfa4f345d6dde55d5..4afa2692f3c573048591cda536def7f1a982e07a 100644
--- a/include/AutoencoderModel.txx
+++ b/include/AutoencoderModel.txx
@@ -395,9 +395,11 @@ void AutoencoderModel<TInputValue,NeuronType>
 		data = net.encode(data);    
 	}
 	*/
-	data = m_net.evalLayer( m_net.layerMatrices().size()/2 ,data);   // features layer for a network containing the encoder and decoder part
+	data = m_net.evalLayer( m_net.layerMatrices().size()/2-1 ,data);   // features layer for a network containing the encoder and decoder part
+	std::cout << data.element(0) << std::endl;
 	unsigned int id = startIndex;
 	target.SetSize(this->m_Dimension);
+	
 	for(const auto& p : data.elements())
 	{
 		for(unsigned int a = 0; a < this->m_Dimension; ++a){
diff --git a/include/DimensionalityReductionModelFactory.txx b/include/DimensionalityReductionModelFactory.txx
index fb65be910ec931cc5b86a6be1c659babe1b33ac5..42eb47e76c8be9d44e53e3032e4af7e55ddae531 100644
--- a/include/DimensionalityReductionModelFactory.txx
+++ b/include/DimensionalityReductionModelFactory.txx
@@ -46,7 +46,7 @@ using TiedAutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTa
 */
 
 template <class TInputValue, class TTargetValue>
-using AutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTargetValue, shark::TanhNeuron>  ;
+using AutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTargetValue, shark::LinearNeuron>  ;
 
 
 template <class TInputValue, class TTargetValue>
diff --git a/include/cbLearningApplicationBaseDR.h b/include/cbLearningApplicationBaseDR.h
index 084db66a4caab98a4dfffc51745c099c4dd16c90..5814c3f3b555fd019a1d7c9da486b0fe8747ec79 100644
--- a/include/cbLearningApplicationBaseDR.h
+++ b/include/cbLearningApplicationBaseDR.h
@@ -103,7 +103,7 @@ public:
 #ifdef OTB_USE_SHARK
 
 	// typedef shark::Autoencoder< shark::TanhNeuron, shark::LinearNeuron> AutoencoderType;
-	typedef shark::TanhNeuron NeuronType;
+	typedef shark::LinearNeuron NeuronType;
 	typedef otb::AutoencoderModel<InputValueType, NeuronType> AutoencoderModelType;
 	/*
 	// typedef shark::TiedAutoencoder< shark::TanhNeuron, shark::LinearNeuron> TiedAutoencoderType;