diff --git a/src/cnn/backpropagation.c b/src/cnn/backpropagation.c
index 5950891..339482d 100644
--- a/src/cnn/backpropagation.c
+++ b/src/cnn/backpropagation.c
@@ -87,7 +87,7 @@ void backward_linearisation(Kernel_nn* ker, float*** input, float*** input_z, fl
         for (int k=0; k < dim_input; k++) {
             for (int l=0; l < dim_input; l++) {
                 for (int j=0; j < size_output; j++) {
-                    ker->d_weights[cpt][j] += input[i][k][l]*output[j]/(depth_input*dim_input*dim_input*size_output);
+                    ker->d_weights[cpt][j] += input[i][k][l]*output[j]/nb_elem;
                 }
                 cpt++;
             }
diff --git a/src/cnn/utils.c b/src/cnn/utils.c
index 30c3410..bf79217 100644
--- a/src/cnn/utils.c
+++ b/src/cnn/utils.c
@@ -124,12 +124,14 @@ Network* copy_network(Network* network) {
     for (int i=0; i < size-1; i++) {
         network_cp->kernel[i] = (Kernel*)nalloc(sizeof(Kernel));
         if (!network->kernel[i]->nn && !network->kernel[i]->cnn) { // Cas de la couche de linéarisation
+            copyVar(kernel[i]->pooling);
             copyVar(kernel[i]->activation);
             copyVar(kernel[i]->linearisation); // 1
             network_cp->kernel[i]->cnn = NULL;
             network_cp->kernel[i]->nn = NULL;
         }
         else if (!network->kernel[i]->cnn) { // Cas du NN
+            copyVar(kernel[i]->pooling);
             copyVar(kernel[i]->activation);
             copyVar(kernel[i]->linearisation); // 0
 
@@ -161,6 +163,7 @@ Network* copy_network(Network* network) {
             }
         }
         else { // Cas du CNN
+            copyVar(kernel[i]->pooling);
             copyVar(kernel[i]->activation);
             copyVar(kernel[i]->linearisation); // 0