diff --git a/include/aidge/operator/Conv.hpp b/include/aidge/operator/Conv.hpp
index 283d0136e50e7c051061acb5274e98368b3d26a2..0db1e8343ff2740921bd7e9729b8a2742da31d85 100644
--- a/include/aidge/operator/Conv.hpp
+++ b/include/aidge/operator/Conv.hpp
@@ -12,6 +12,7 @@
 #ifndef AIDGE_CORE_OPERATOR_CONV_H_
 #define AIDGE_CORE_OPERATOR_CONV_H_
 
+#include <algorithm>
 #include <array>
 #include <cstddef>  // std::size_t
 #include <string>
@@ -234,10 +235,16 @@ std::shared_ptr<Node> Conv(DimSize_t inChannels,
                            bool noBias = false);
 
 /**
- * @brief Helper function for Conv with C-style arrays.
+ * @brief Perform a convolution on the input Tensor.
  *
- * This helper function allows automatic template deduction of the number of dimensions (DIM)
- * based on the kernel dimensions provided.
+ * @tparam DIM Number of dimensions for the feature map.
+ * @param inChannels Number of input channels.
+ * @param outChannels Number of output channels.
+ * @param kernelDims Dimensions of the kernel. Must be the same number of dimensions as the feature map.
+ * @param name Name of the operator.
+ * @param strideDims Dimensions of the stride attribute. Must be the same number of dimensions as the feature map.
+ * @param dilationDims Dimensions of the dilation attribute. Must be the same number of dimensions as the feature map.
+ * @return std::shared_ptr<Node> A Node containing the operator.
  */
 template <DimSize_t DIM>
 std::shared_ptr<Node> Conv(
diff --git a/src/operator/Conv.cpp b/src/operator/Conv.cpp
index 8d5f3332218c9fb0dbdb9398de254cfcccae9d7e..3abd144f882a02c271f072b963714351f2dcaf47 100644
--- a/src/operator/Conv.cpp
+++ b/src/operator/Conv.cpp
@@ -237,6 +237,21 @@ std::shared_ptr<Aidge::Node> Aidge::Conv(
     const std::array<Aidge::DimSize_t, DIM> &dilationDims,
     bool noBias)
 {
+    AIDGE_ASSERT(DIM<=MaxDim,"{}: Too many kernel dimensions required, maximum allowed : {} ", Conv_Op<DIM>::Type, MaxDim);
+    AIDGE_ASSERT(!std::any_of(dilationDims.cbegin(),
+                              dilationDims.cend(),
+                              [](DimSize_t val) { return val == 0; }),
+                 "Conv : at least of of the dilation dimension is 0, expecting "
+                 "strictly positive values. Got {}",
+                 Conv_Op<DIM>::Type,
+                 dilationDims);
+    AIDGE_ASSERT(!std::any_of(strideDims.cbegin(),
+                              strideDims.cend(),
+                              [](DimSize_t val) { return val == 0; }),
+                 "{}: at least one of the stride dimension is 0, expecting "
+                 "strictly positive values. Got {}.",
+                 Conv_Op<DIM>::Type,
+                 strideDims);
     static_assert(DIM<=MaxDim,"Too many kernel dimensions required by Conv, not supported");
     return Conv(inChannels, outChannels, to_array(kernelDims), name, strideDims, dilationDims, noBias);
 }